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Sneha Kanchukatla
Telangana, India0 followers0 following
- About
- High School
- Bachelor's
- Target
- GRE
Female
Telangana, India
Work ExperienceSneha Kanchukatla has not added any work experience details yet.
ProjectsOBJECT DETECTION AND CLASSIFICATION USING YOLO
Role - TEAM LEAD
for Industrial
Feb 1, 2022 - Apr 15, 2022
Classification is a systematic arrangement in groups and categories based on its features. Image classification came into existence for decreasing the gap between the computer vision and human vision by training the computer with the data. The image classification is achieved by differentiating the image into the prescribed category based on the content of the vision. Motivation by , in this paper, we explore the study of image classification using deep learning. The conventional methods used for image classifying is part and piece of the field of artificial intelligence (AI) formally called as machine learning. The machine learning consists of feature extraction module that extracts the important features such as edges, textures etc and a classification module that classify based on the features extracted. The main limitation of machine learning is, while separating, it can only extract certain set of features on images and unable to extract differentiating features from the training set of data. This disadvantage is rectified by using the deep learning . Deep learning (DL) is a sub field to the machine learning, capable of learning through its own method of computing. A deep learning model is introduced to persistently break down information with a homogeneous structure like how a human would make determinations. To accomplish this, deep learning utilizes a layered structure of several algorithms expressed as an artificial neural system (ANN). The architecture of an ANN is simulated with the help of the biological neural network of the human brain. This makes the deep learning most capable than the standard machine learning models . In deep learning, we consider the neural networks that identify the image based on its features.
IOT BASED AQUACULTURE MONITORING
Role - TEAM LEAD
for Industrial
Dec 5, 2021 - Dec 20, 2021
Aquaculture is one of the prospering segments in developing countries like India because it contributes 1.07 percent of the GDP. It is found that fish necessity of the country by 2025 would be in terms of 1.6 crores tones and thanks to the overfishing regular fisheries are drained therefore commercial aquaculture has been appeared. Aquaculture comprises the arrangement of exercises, information and methods for the rearing of underwater plants and a couple of sorts of animals within the water. This action has incredible significance in monetary advancement and food
development. Shrimp culture habitat comprise parameters like temperature, humidity, soil composition, nutrification,
biological oxygen demand, chemical oxygen demand which are requirements of shrimp culture. Due to high price and demand, many farmers in coastal region are shifting from vegetation to shrimp culture. Shrimp cultivation is encountered with abnormalities in temperature, soil composition, BOD, COD, pH and sophisticated problems like slow growth diseases, nutritional imbalances, pathogenic
diseases can downfall yields of cultivation. Both WSN and IoT revolutionized through remote sensing with centralized monitoring of agriculture, fisheries and Industrial processing. This paper presents a prototype design monitoring the shrimp culture parameters like temperature, pH, DO, etc. The prototype design will improve the practice of conventional Shrimp culture by remote sensing monitoring system and this is able to substantially increase the yield of the shrimp. The prototype was implemented and tested by deploying in pond for at some point . The variation of parameters is measured by using fixing a ThingSpeak
channel. The results show that the system is capable is monitoring the essential parameters and any change within
the se parameters resulting in abnormal conditions in the pond are often easily communicated with the concerned person through message.
Research PapersSneha Kanchukatla has not added any research paper yet.
VolunteeringSneha Kanchukatla has not added any volunteering detail yet.