Aryaman Pattnayak

Bachelor of Technology - BTech, Computer Science

AI/ML Specialist, Data science, Data Analytics

Aryaman Pattnayak is a Tech writer based in Bhubaneswar, India. His academic background is in Computer Science and Engineering. Aryaman is passionate about leveraging technology for innovation and has a keen interest in Artificial Intelligence, Machine Learning, and Data Science.

Aryaman’s work encompasses several topics, including "FinGPT" and "Financial Fraud Detection," reflecting his dedication to practical AI solutions. Outside of his professional pursuits, Aryaman finds joy in sharing insights through Medium and exploring the convergence of technology and finance. In his free time, he enjoys various hobbies, including reading and listening to music.

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Articles from Aryaman

RECAP: Elevating Audio Captioning with Retrieval-Augmented Models

Researchers from the University of Maryland introduce RECAP, a groundbreaking approach in audio captioning. RECAP leverages retrieval-augmented generation to enhance cross-domain generalization, excelling in describing complex audio environments, novel sound events, and compositional audios. This innovation promises a significant step forward in diverse applications, from smart cities to industrial monitoring, by addressing domain shift challenges in audio captioning.

22 Sep 2023

Deep Learning-based Multimodal Emotion Recognition: Challenges and Future Prospects

This comprehensive review explores the application of deep learning in multimodal emotion recognition (MER), covering audio, visual, and text modalities. It discusses deep learning techniques, challenges, and future directions in this field, emphasizing the need for lightweight architectures, interpretable models, diverse datasets, and rigorous real-world testing to advance human-centric AI technologies and interactive systems.

21 Sep 2023

AI's Potential in Revolutionizing Iron Disorder Management

A recent review explores the potential of artificial intelligence (AI) in revolutionizing the screening, diagnosis, and monitoring of body iron levels. The review reveals AI's promise in improving the management of iron deficiency and overload, although challenges such as data limitations and ethical concerns must be addressed for its full potential to be realized.

20 Sep 2023

Revolutionizing Date Palm Health: A New AI Algorithm for SDS Detection

Researchers have developed the FFMKO algorithm, a powerful tool for the early detection of Sudden Decline Syndrome (SDS) in date palm trees. By combining image enhancement, thresholding, and clustering techniques, this algorithm achieved an impressive accuracy rate of over 94%, offering a promising solution to combat the devastating effects of SDS on date palm crops.

19 Sep 2023

ClueCatcher: A Robust Approach to Detect Deepfakes

Researchers introduce ClueCatcher, an innovative method for detecting deepfakes. By analyzing inconsistencies and disparities introduced during facial manipulation, ClueCatcher identifies subtle artifacts, achieving high accuracy and cross-dataset generalizability. This research addresses the growing threat of increasingly deceptive deepfakes and highlights the importance of automated detection methods that do not rely on human perception.

17 Sep 2023

AI Chatbots Enhance Sustainable Supply Chains in Indian SMEs

Researchers explore how AI chatbots can improve supply chain sustainability in small and medium manufacturing enterprises (SMEs) in India. The research shows that chatbots enhance supply chain visibility and innovation capability, leading to improved sustainability performance, and offers practical recommendations for SMEs to leverage this technology for sustainable practices.

17 Sep 2023

Navigating Metro Peak Hours: Machine Learning Sheds Light on Deviation Patterns

Researchers investigate the often-overlooked phenomenon of peak hour deviation in metro stations, where the busiest times differ from the overall network peak. Using advanced machine learning techniques, the research reveals the factors influencing these deviations, providing valuable insights for more accurate capacity planning and avoiding mismatches between projected and actual demands in metro systems.

15 Sep 2023

Bridging Nature and Technology: The Synergistic Future of AI and Ecology

This study advocates for a closer collaboration between artificial intelligence (AI) and ecological research to address pressing challenges such as climate change. The authors highlight the potential for AI to learn from ecological systems and propose a convergence that can lead to groundbreaking discoveries and more resilient AI systems.

14 Sep 2023

Empathy Matters: How Chatbots Can Influence Tourists' Destination Choices

Researchers reveal that chatbots equipped with empathetic capabilities significantly impact tourists' satisfaction and their intention to visit a destination. Empathy emerged as the most crucial attribute, surpassing informativeness and interactivity, highlighting the importance of emotionally resonant interactions in the tourism sector.

13 Sep 2023

ROMAN: Advancing Robots with a Hybrid Hierarchical Learning Framework

This study introduces ROMAN, a groundbreaking hybrid hierarchical learning framework for robots. ROMAN combines imitation and reinforcement learning to enable robots to solve complex, multi-step manipulation tasks, exhibit adaptability in randomized scenarios, and recover from failures, marking a significant leap in the field of embodied AI.

12 Sep 2023