Deep Intelligence Learning Lab (DiL Lab)’s Post

I am thrilled to share the exciting news that my student, Anagha Muralidharan, who is pursuing a data science minor, has successfully published her research in the renowned journal Physiology & Behavior. This publication results from a strong collaborative effort with Dr. Amrutha Swaminathan from the Molecular Neurodevelopment Lab, School of Biology, IISER TVM. Anagha's dedication and hard work have led to this remarkable achievement, highlighting her growing expertise in applying data science techniques to biological research. I extend my heartfelt congratulations to Anagha for her outstanding contributions to this research. I also want to sincerely thank Dr. Amrutha Swaminathan for her unwavering support and invaluable guidance throughout this collaborative project. This accomplishment is a testament to the power of interdisciplinary collaboration and the potential of combining data science with biological research for meaningful scientific advancements. #zebrafish #AI #research #datascience #biology

I am delighted to welcome my first PhD student, Ms Anjali Jain, to the Deep Intelligence Learning Lab (DiL Lab) @IISER TVM. Anjali joins us with a solid academic background, earning her master's in Mathematics and Computing from Banaras Hindu University (BHU). During her studies, she specialized in Deep Learning, Machine Learning, Statistics, Data Visualization, and Optimization techniques, demonstrating a keen ability to apply these methods to data analysis and computational tasks. Anjali's research interests are deeply rooted in medical image analysis, where she is passionate about tackling complex challenges. Her commitment to leveraging machine learning for significant advancements in healthcare aligns perfectly with our lab's mission. I am confident that Anjali's expertise, enthusiasm, and dedication will contribute significantly to our research. I look forward to supporting her as she embarks on this exciting PhD journey.

I am happy to share that my collaborative research work, "Agricultural Object Detection with You Only Look Once (YOLO) Algorithm: A Bibliometric and Systematic Literature Review," has been published in the Computers and Electronics in Agriculture journal, which boasts an impressive Impact Factor of 8.3 (𝐒𝐂𝐈𝐄, 𝐐𝟏, 𝐇 𝐢𝐧𝐝𝐞𝐱 168). This publication is a testament to the power of teamwork and shared vision in advancing agricultural technology. I would like to extend my heartfelt thanks to Dr. Chetan Badgujar for inviting me to collaborate on this important research project. His expertise and guidance were invaluable in the development of this work. Paper Link: https://lnkd.in/gH-AUfEA Highlights -We conducted a quantitative and qualitative review of YOLO application in agriculture. -YOLO modification and integration were discussed to solve task-specific challenges. -YOLO-based tools and technologies show potential for agricultural task automation. -This detailed documentation will advance existing knowledge of YOLO in agriculture. -The study will benefit the multidisciplinary agricultural community.