A5049194814- Remote Sensing in Agriculture
- Remote-Sensing Image Classification
- IoT and GPS-based Vehicle Safety Systems
- Remote Sensing and Land Use
- Network Security and Intrusion Detection
- Smart Agriculture and AI
- Hydrological Forecasting Using AI
- Impact of AI and Big Data on Business and Society
- Water Quality and Pollution Assessment
- Human-Automation Interaction and Safety
- Anomaly Detection Techniques and Applications
- Fire Detection and Safety Systems
- Land Use and Ecosystem Services
- Advanced Neural Network Applications
- Human Mobility and Location-Based Analysis
- Food Supply Chain Traceability
- Human Motion and Animation
- Traffic Prediction and Management Techniques
- Energy Efficient Wireless Sensor Networks
- Water Quality Monitoring Technologies
- IoT-based Smart Home Systems
- Advanced Image and Video Retrieval Techniques
- Video Analysis and Summarization
- Biological and pharmacological studies of plants
- Internet Traffic Analysis and Secure E-voting
Gujarat Technological University
2023-2024
Mitra Biotech (India)
2023
Classification of objects into their specific classes is always been significant tasks machine learning. As the study flower, categorizing class flower important subject in field Botany but similarity between diverse species flowers, texture and color dissimilarities amongst same there still are some challenges recognition images. Existing recent Google's inception-v3 model comparatively takes more time space for classification with high accuracy. In this paper, we have shown experimental...
Abstract Water is a crucial and indispensable resource for sustaining human life, maintaining its quality of utmost importance the well-being individuals. When drinking water becomes contaminated, it poses severe health risks, including diseases like diarrhea, cholera, various other waterborne ailments. As result, ensuring safe clean to promote public health. Recent findings indicate that significant number approximately 3,575,000 people lose their lives each year due water-related...
Change detection is one of the crucial aspects analyzing dynamic changes in various land cover types, especially case cropland. With increasing availability high-resolution remote sensing data, different deep learning techniques have emerged as an effective means for accurately detecting changes. Detecting intraclass variations main challenge cropland change detection, apart from crop phenology, shadow, and illumination effects. Here, a novel image pre-processing technique introduced to help...
LSTM is a valuable approach in the context of land cover change detection due to its ability capture temporal dependencies and long-term patterns sequential data. Land involves analyzing satellite images or time series data identify classify changes surface features over time. By step analysis images, can even small gradual area. The recurrent nature allows it understand relationship between neighboring pixels which could also help fix missing noise pixel if any. Lastly, feature extraction...
Startup companies are an essential element of the contemporary corporate environment, serving as a significant driver both technological advancement and economic expansion. On other hand, large percentage these new businesses never attain sustained success, which is why it crucial to precisely anticipate their future possibilities. It may be difficult for startups thrive, grow, accomplish goals if they do not have access sufficient money investments. The amount invested, funded, achievements...