scholarly journals Large-Scale Person Re-Identification Based on Deep Hash Learning

Entropy ◽  
2019 ◽  
Vol 21 (5) ◽  
pp. 449 ◽  
Author(s):  
Xian-Qin Ma ◽  
Chong-Chong Yu ◽  
Xiu-Xin Chen ◽  
Lan Zhou
Keyword(s):  
Hash Function ◽  
Large Scale ◽  
Research Topic ◽  
Cross Entropy ◽  
Network Layers ◽  
Hash Code ◽  
Image Hash ◽  
Challenging Research ◽  
Fully Connected ◽  
Relationship Of

Person re-identification in the image processing domain has been a challenging research topic due to the influence of pedestrian posture, background, lighting, and other factors. In this paper, the method of harsh learning is applied in person re-identification, and we propose a person re-identification method based on deep hash learning. By improving the conventional method, the method proposed in this paper uses an easy-to-optimize shallow convolutional neural network to learn the inherent implicit relationship of the image and then extracts the deep features of the image. Then, a hash layer with three-step calculation is incorporated in the fully connected layer of the network. The hash function is learned and mapped into a hash code through the connection between the network layers. The generation of the hash code satisfies the requirements that minimize the error of the sum of quantization loss and Softmax regression cross-entropy loss, which achieve the end-to-end generation of hash code in the network. After obtaining the hash code through the network, the distance between the pedestrian image hash code to be retrieved and the pedestrian image hash code library is calculated to implement the person re-identification. Experiments conducted on multiple standard datasets show that our deep hashing network achieves the comparable performances and outperforms other hashing methods with large margins on Rank-1 and mAP value identification rates in pedestrian re-identification. Besides, our method is predominant in the efficiency of training and retrieval in contrast to other pedestrian re-identification algorithms.

scholarly journals Discrete Semantics-Guided Asymmetric Hashing for Large-Scale Multimedia Retrieval

2021 ◽  
Vol 11 (18) ◽  
pp. 8769
Author(s):  
Jun Long ◽  
Longzhi Sun ◽  
Liujie Hua ◽  
Zhan Yang
Keyword(s):  
Code Generation ◽  
Hash Function ◽  
Large Scale ◽  
Semantic Information ◽  
Multimedia Data ◽  
Multimedia Retrieval ◽  
Coordinate Descent Algorithm ◽  
Hash Code ◽  
Benchmark Datasets ◽  
Hash Codes

Cross-modal hashing technology is a key technology for real-time retrieval of large-scale multimedia data in real-world applications. Although the existing cross-modal hashing methods have achieved impressive accomplishment, there are still some limitations: (1) some cross-modal hashing methods do not make full consider the rich semantic information and noise information in labels, resulting in a large semantic gap, and (2) some cross-modal hashing methods adopt the relaxation-based or discrete cyclic coordinate descent algorithm to solve the discrete constraint problem, resulting in a large quantization error or time consumption. Therefore, in order to solve these limitations, in this paper, we propose a novel method, named Discrete Semantics-Guided Asymmetric Hashing (DSAH). Specifically, our proposed DSAH leverages both label information and similarity matrix to enhance the semantic information of the learned hash codes, and the ℓ2,1 norm is used to increase the sparsity of matrix to solve the problem of the inevitable noise and subjective factors in labels. Meanwhile, an asymmetric hash learning scheme is proposed to efficiently perform hash learning. In addition, a discrete optimization algorithm is proposed to fast solve the hash code directly and discretely. During the optimization process, the hash code learning and the hash function learning interact, i.e., the learned hash codes can guide the learning process of the hash function and the hash function can also guide the hash code generation simultaneously. Extensive experiments performed on two benchmark datasets highlight the superiority of DSAH over several state-of-the-art methods.

Character Reorganization and Categorization using Hybrid Algorithms by Scanned Documents

2019 ◽  
Vol 8 (6S2) ◽  
pp. 943-948
Keyword(s):  
Research Work ◽  
Hybrid Algorithms ◽  
Research Topic ◽  
Image Processing Techniques ◽  
Digital Books ◽  
Otsu Method ◽  
Challenging Research ◽  
Processing Techniques ◽  
Scanned Documents ◽  
Day By Day

Detection and reorganization of text may save a lot of time while reproducing old books text and its chapters. This is really challenging research topic as different books may have different font types and styles. The digital books and eBooks reading habit is increasing day by day and new documents are producing every day. So in order to boost the process the text reorganization using digital image processing techniques can be used. This research work is using hybrid algorithms and morphological algorithms. For sample we have taken an letter pad where the text and images are separated using algorithms. The another objective of this research is to increase the accuracy of recognized text and produce accurate results. This research worked on two different concepts, first is concept of Pixel-level thresholding processing and another one is Otsu Method thresholding.

scholarly journals Synthesis of Metal Organic Frameworks by Ball-Milling

Crystals ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 15
Author(s):  
Cheng-An Tao ◽  
Jian-Fang Wang
Keyword(s):  
Ball Milling ◽  
Large Scale ◽  
Raw Materials ◽  
Metal Organic Frameworks ◽  
Research Topic ◽  
Mass Ratio ◽  
Time Consumption ◽  
Metal Organic ◽  
Short Time ◽  
Made In

Metal-organic frameworks (MOFs) have been used in adsorption, separation, catalysis, sensing, photo/electro/magnetics, and biomedical fields because of their unique periodic pore structure and excellent properties and have become a hot research topic in recent years. Ball milling is a method of small pollution, short time-consumption, and large-scale synthesis of MOFs. In recent years, many important advances have been made. In this paper, the influencing factors of MOFs synthesized by grinding were reviewed systematically from four aspects: auxiliary additives, metal sources, organic linkers, and reaction specific conditions (such as frequency, reaction time, and mass ratio of ball and raw materials). The prospect for the future development of the synthesis of MOFs by grinding was proposed.

scholarly journals GateRL: Automated Circuit Design Framework of CMOS Logic Gates Using Reinforcement Learning

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1032
Author(s):  
Hyoungsik Nam ◽  
Young In Kim ◽  
Jina Bae ◽  
Junhee Lee
Keyword(s):  
Reinforcement Learning ◽  
Circuit Design ◽  
Logic Gates ◽  
Connection Matrix ◽  
Design Framework ◽  
Network Layers ◽  
Learning Speed ◽  
Fully Connected ◽  
Automated Circuit Design ◽  
Circuit Configuration

This paper proposes a GateRL that is an automated circuit design framework of CMOS logic gates based on reinforcement learning. Because there are constraints in the connection of circuit elements, the action masking scheme is employed. It also reduces the size of the action space leading to the improvement on the learning speed. The GateRL consists of an agent for the action and an environment for state, mask, and reward. State and reward are generated from a connection matrix that describes the current circuit configuration, and the mask is obtained from a masking matrix based on constraints and current connection matrix. The action is given rise to by the deep Q-network of 4 fully connected network layers in the agent. In particular, separate replay buffers are devised for success transitions and failure transitions to expedite the training process. The proposed network is trained with 2 inputs, 1 output, 2 NMOS transistors, and 2 PMOS transistors to design all the target logic gates, such as buffer, inverter, AND, OR, NAND, and NOR. Consequently, the GateRL outputs one-transistor buffer, two-transistor inverter, two-transistor AND, two-transistor OR, three-transistor NAND, and three-transistor NOR. The operations of these resultant logics are verified by the SPICE simulation.

scholarly journals Obsidian and Obsidian-like Glass Tesserae: A Multidisciplinary Approach to Study the Dedication Wall Mosaic in the Church of St. Mary of the Admiral in Palermo (12th Century)

2020 ◽  
Vol 6 (1) ◽  
pp. 403-416
Author(s):  
Valentina Cantone ◽  
Rita Deiana ◽  
Alberta Silvestri ◽  
Ivana Angelini
Keyword(s):  
Multidisciplinary Approach ◽  
Multispectral Imaging ◽  
Volcanic Glass ◽  
Research Topic ◽  
Multidisciplinary Study ◽  
12Th Century ◽  
Challenging Research ◽  
Byzantine Period ◽  
Dark Glass ◽  
The Church

AbstractPliny the Elder testifies that roman workshops used volcanic glass (obsidian), but also produced and used a dark glass (obsidian-like glass) quite similar to the natural one. In the context of the study on medieval mosaics, the use of the obsidian and obsidian-like tesserae is a challenging research topic. In this paper, we present the results of a multidisciplinary study carried out on the Dedication wall mosaic, realized by a byzantine workshop in the 12th century in the Church of St. Mary of the Admiral in Palermo, and where numerous black-appearing tesserae, supposed to be composed of obsidian by naked-eyes observation, are present. Historical documents, multispectral imaging of the wall mosaic, and some analytical methods (SEM-EDS and XRPD) applied to a sample of black tesserae, concur in identifying here the presence of obsidian and different obsidian-like glass tesserae. This evidence, although related to the apparent tampering and restoration, could open a new scenario in the use of obsidian and obsidian-like glass tesserae during the Byzantine period in Sicily and in the reconstruction of multiple restoration phases carried out between 12th and 20th century AD on the mosaics of St. Mary of the Admiral.

scholarly journals Geo-Spatial Analysis of Population Density and Annual Income to Identify Large-Scale Socio-Demographic Disparities

2021 ◽  
Vol 10 (7) ◽  
pp. 432
Author(s):  
Nicolai Moos ◽  
Carsten Juergens ◽  
Andreas P. Redecker
Keyword(s):  
Population Density ◽  
Large Scale ◽  
Methodological Approach ◽  
Spatial Relationship ◽  
Postal Code ◽  
Annual Income ◽  
Choropleth Maps ◽  
Clustering Approach ◽  
Relationship Of ◽  
Insight Into

This paper describes a methodological approach that is able to analyse socio-demographic and -economic data in large-scale spatial detail. Based on the two variables, population density and annual income, one investigates the spatial relationship of these variables to identify locations of imbalance or disparities assisted by bivariate choropleth maps. The aim is to gain a deeper insight into spatial components of socioeconomic nexuses, such as the relationships between the two variables, especially for high-resolution spatial units. The used methodology is able to assist political decision-making, target group advertising in the field of geo-marketing and for the site searches of new shop locations, as well as further socioeconomic research and urban planning. The developed methodology was tested in a national case study in Germany and is easily transferrable to other countries with comparable datasets. The analysis was carried out utilising data about population density and average annual income linked to spatially referenced polygons of postal codes. These were disaggregated initially via a readapted three-class dasymetric mapping approach and allocated to large-scale city block polygons. Univariate and bivariate choropleth maps generated from the resulting datasets were then used to identify and compare spatial economic disparities for a study area in North Rhine-Westphalia (NRW), Germany. Subsequently, based on these variables, a multivariate clustering approach was conducted for a demonstration area in Dortmund. In the result, it was obvious that the spatially disaggregated data allow more detailed insight into spatial patterns of socioeconomic attributes than the coarser data related to postal code polygons.

Metal–organic frameworks as catalytic selectivity regulators for organic transformations

2021 ◽  
Author(s):  
Jun Guo ◽  
Yutian Qin ◽  
Yanfei Zhu ◽  
Xiaofei Zhang ◽  
Chang Long ◽  
...  
Keyword(s):  
Heterogeneous Catalysts ◽  
Metal Organic Frameworks ◽  
Research Topic ◽  
Organic Transformations ◽  
Catalytic Selectivity ◽  
Challenging Research ◽  
Metal Organic

Selective organic transformations using metal–organic frameworks (MOFs) and MOF-based heterogeneous catalysts have been an intriguing but challenging research topic in both the chemistry and materials communities.

The study of mixed assets allocation based on Black–Litterman model

2021 ◽  
pp. 2150022
Author(s):  
Jianwu Lin ◽  
Mengwei Tang ◽  
Jiachang Wang ◽  
Ping He
Keyword(s):  
Stock Market ◽  
Asset Allocation ◽  
Private Equity ◽  
Equity Market ◽  
Research Topic ◽  
Allocation Model ◽  
Quantitative Models ◽  
Challenging Research ◽  
Qualitative Models ◽  
New Type

With Private Funds having a new type of license for asset allocation practice in China, comprehensive asset allocation cross private equity and stock market has received more attention. However, most of the studies focus more on the stock market, and asset allocation models for private equity market that are mainly made based on experience. Thus, the joint allocation of assets crosses both markets making it a challenging research topic. This paper introduces the Black–Litterman model into the private equity market, realizing the transition from qualitative models to quantitative models. It lays a solid quantitative ground for the mixed asset allocation model in both the markets.

scholarly journals The power of materialism among young adults: exploring the effects of values on impulsiveness and responsible financial behavior

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Andrea Lučić ◽  
Marija Uzelac ◽  
Andrea Previšić
Keyword(s):  
Young Adults ◽  
Large Scale ◽  
Brand Management ◽  
Mediating Effect ◽  
Financial Behavior ◽  
Purchase Decisions ◽  
Content Type ◽  
Financial Behaviour ◽  
Relationship Of ◽  
The Relationship

Purpose The purpose of this paper is to investigate the effects of values of materialism on cognitive and affective impulsiveness and responsible financial behavior among young adults. Design/methodology/approach A large-scale study (n = 483) was conducted on a sample of young adults 18 to 25 years of age in Croatia. Findings The research found that materialism has no direct effect on responsible financial behaviour (RFB), however, cognitive impulsiveness fully mediates the relationship of all three there three elements of materialism, centrality, success and happiness and RFB. Affective impulsiveness has no effect on the relationship. Furthermore, only materialism as centrality strongly and positively influences cognitive and affective impulsiveness. Practical implications Presented conclusions could be used by policymakers as guidelines for developing educational plans and curriculum to build financial capability and consumer protection among young adults and could be helpful for brand management activities targeting young people purchase decisions. Originality/value This paper’s ultimate purpose is to uncover the mechanism and the power of materialism on impulsiveness and responsible financial behavior. The paper’s originality is established by the focus on the investigation of materialism as an antecedent factor of impulsiveness and by questioning the nature of the relationship between materialism and responsible financial behavior through the mediating effect of impulsiveness.

Sign in / Sign up

Export Citation Format

Share Document