Object Detection Based on Teachable Machine

2021 ◽  
Vol 7 (2) ◽  
Author(s):  
Midhun P Mathew ◽  
Therese Yamuna Mahesh
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Object Detection ◽  
Plant Diseases ◽  
Small Project ◽  
Special Knowledge

We are living in an era of wonderful events in Artificial Intelligence every day. Machine learning and computers make our work easier in several domains. Object detection is one area which greq by leaps and bounds with the advent of AI. This paper explains about a teachable machine of google which can be used by people whose have no special knowledge of AI and Machine Learning. This technology is introduced by google to help students as well as any person who has interest in studying machine learning. In this paper, we are explaining this concept with a small project to identify different classes of plant diseases using teachable machine.

Object Detection in Fog Computing Using Machine Learning Algorithms

2020 ◽  
pp. 90-107
Author(s):  
Peyakunta Bhargavi ◽  
Singaraju Jyothi
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Object Detection ◽  
Fog Computing ◽  
Machine Learning Algorithms ◽  
Sensor Data ◽  
Core Network ◽  
The Core ◽  
The Moment ◽  
Algorithmic Approaches

The moment we live in today demands the convergence of the cloud computing, fog computing, machine learning, and IoT to explore new technological solutions. Fog computing is an emerging architecture intended for alleviating the network burdens at the cloud and the core network by moving resource-intensive functionalities such as computation, communication, storage, and analytics closer to the end users. Machine learning is a subfield of computer science and is a type of artificial intelligence (AI) that provides machines with the ability to learn without explicit programming. IoT has the ability to make decisions and take actions autonomously based on algorithmic sensing to acquire sensor data. These embedded capabilities will range across the entire spectrum of algorithmic approaches that is associated with machine learning. Here the authors explore how machine learning methods have been used to deploy the object detection, text detection in an image, and incorporated for better fulfillment of requirements in fog computing.

scholarly journals Machine Learning for Detection of Palm Oil Leaf Disease Visually using Convolutional Neural Network Algorithm

2021 ◽  
Vol 4 (2) ◽  
pp. 286-293
Author(s):  
Asrianda Asrianda ◽  
Hafizh Al Kautsar Aidilof ◽  
Yoga Pangestu
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Machine Learning ◽  
Computer Vision ◽  
Object Detection ◽  
Convolutional Neural Network ◽  
Image Classification ◽  
Palm Oil ◽  
Leaf Disease ◽  
Neural Network Algorithm

Artificial intelligence (AI) merupakan bidang ilmu pengetahuan yang saat ini menjadi isu yang menarik dan masih diteliti secara luas. Salah satu cabang dari pengembangan AI adalah computer vision yang di dalamnya terdapat topik pembahasan image classification dan object detection. Machine learning dapat dimanfaatkan di dalam bidang computer vision untuk melakukan object detection dan image classification, yaitu dengan menggunakan algoritma Convolutional Neural Network (CNN). CNN banyak digunakan pada penelitian terdahulu karena akurasinya yang tinggi. Pada penelitian ini, CNN digunakan untuk mendeteksi jenis penyakit daun tanaman kelapa sawit, dengan dataset sebanyak 60 gambar, dimana 50 diantaranya merupakan daun dengan 5 jenis penyakit berbeda, yaitu Curvularia sp, Cochliobolus carbonus, Capnodium sp, Drecshlera, dan defisiensi unsur hara. Sedangkan 10 sisanya merupakan gambar daun sehat. Hasilnya, CNN dapat mendeteksi penyakit daun kelapa sawit dengan akurasi yang dihasilkan mencapai 99%.

scholarly journals Managing Social Distancing using Smart Detector

2021 ◽  
Vol 1 (2) ◽  
pp. 1-10
Author(s):  
Saurabh Yadav ◽  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Object Detection ◽  
Real Time ◽  
Social Distance ◽  
Learning Models ◽  
Social Distancing ◽  
Detection Model

This paper presents a methodology for social distance detection using deep learning models and algorithms such as YOLO and CNN. Deep learning is one of those technologies which have greatly enhanced the overall experience of the technology that humans use. Deep learning has brought a lot of changes from self-driven cars made by Tesla to the smallest object detection model. Deep learning, artificial intelligence, and machine learning provide a way to be able to put things to use. The purpose of this paper is to be able to implement real-time object detection to detect social distancing.

Machine Learning in Agriculture

2018 ◽  
Vol 8 (6) ◽  
pp. 26 ◽  
Author(s):  
Matthew N. O. Sadiku ◽  
Chandra M. M Kotteti ◽  
Sarhan M. Musa
Keyword(s):  
Climate Change ◽  
Artificial Intelligence ◽  
Machine Learning ◽  
Disease Diagnosis ◽  
Automated Detection ◽  
Disease Prediction ◽  
Paper Briefly ◽  
Agriculture Sector ◽  
Modern Agriculture ◽  
Crop Disease

Machine learning is an emerging field of artificial intelligence which can be applied to the agriculture sector. It refers to the automated detection of meaningful patterns in a given data.  Modern agriculture seeks ways to conserve water, use nutrients and energy more efficiently, and adapt to climate change.  Machine learning in agriculture allows for more accurate disease diagnosis and crop disease prediction. This paper briefly introduces what machine learning can do in the agriculture sector.

Development of innovative hygienic technologies for preservation of the workers’ reproductive health

2020 ◽  
pp. 792-792
Author(s):  
M. A. Fesenko ◽  
G. V. Golovaneva ◽  
A. V. Miskevich
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Reproductive Health ◽  
Reproductive System ◽  
Preventive Measures ◽  
Learning Algorithms ◽  
Reproductive Function ◽  
Machine Learning Algorithms ◽  
New Model

The new model «Prognosis of men’ reproductive function disorders» was developed. The machine learning algorithms (artificial intelligence) was used for this purpose, the model has high prognosis accuracy. The aim of the model applying is prioritize diagnostic and preventive measures to minimize reproductive system diseases complications and preserve workers’ health and efficiency.

PEMBUATAN PENDETEKSI OBYEK DENGAN METODE YOU ONLY LOOK ONCE (YOLO) UNTUK AUTOMATED TELLER MACHINE (ATM)

2019 ◽  
Vol 17 (1) ◽  
pp. 69-76
Author(s):  
Mohammad Shiddiq Ghozali
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Object Detection ◽  
Open Source ◽  
Automated Teller Machine

Perkembangan Teknologi Informasi dan Komunikasi begitu pesat di zaman sekarang ini. Diikuti pula dengan perkembangan di bidang Artificial Intelligence (AI) atau Kecerdasan Buatan. Di Indonesia sendiri masih belum begitu populer dikalangan masyarakat akan tetapi perusahaan-perusahaan IT berlomba-lomba menciptakan inovasi dibidang Kecerdasan Buatan dan penerapan Kecerdasan Buatan disegala aspek kehidupan. Contoh kasus di Automated Teller Machine (ATM), seringkali terjadi kejahatan di ATM seperti pengintaian nomor pin, skimming, lebanese loop dan kejahatan lainnya. Walaupun di ATM sudah terdapat CCTV akan tetapi penjahat menggunakan alat bantu untuk menutupi wajahnya seperti helm, topi, masker dan kacamata hitam. Biasanya didepan pintu masuk ATM terpampang larangan untuk tidak menggunakan helm, topi, masker dan kacamata hitam serta tidak membawa rokok. Akan tetapi larangan itu masih tetap ada yang melanggar, dikarenakan tidak ada tindak lanjut ketika seseorang menggunakan benda-benda yang dilarang dibawa kedalam ATM. Oleh karena itu penulis membuat sistem pendeteksi obyek di bidang Kecerdasan Buatan untuk mendeteksi benda-benda yang dilarang digunakan ketika berada di ATM. Salah satu metode yang digunakan untuk menciptakan Object Detection yaitu You Only Look Once (YOLO). Implementasi ide ini tersedia pada DARKNET (open source neural network). Cara kerja YOLO yaitu dengan melihat seluruh gambar sekali, kemudian melewati jaringan saraf sekali langsung mendeteksi object yang ada. Oleh karena itu disebut You Only Look Once (YOLO). Pada penelitian ini, penulis membuat sistem yang masih dalam bentuk pengembangan, sehingga menjalankannya masih menggunakan command prompt. Keywords : Automated Teller Machine (ATM), Kecerdasan Buatan, Pendeteksi Obyek, You Only Look Once (YOLO)  

Sign in / Sign up

Export Citation Format

Share Document