no code implementations • 12 Jan 2025 • Aparna Joshi, Kojo Adugyamfi, Jennifer Merickel, Pujitha Gunaratne, Anuj Sharma
This study addresses this need by leveraging Naturalistic Driving Data (NDD) to analyze driving performance measures - specifically, speed limit adherence on interstates and deceleration at stop intersections, both of which may be influenced by age-related declines.
no code implementations • 6 Jan 2025 • Alexandru Buburuzan, Anuj Sharma, John Redford, Puneet K. Dokania, Romain Mueller
Safety-critical applications, such as autonomous driving, require extensive multimodal data for rigorous testing.
no code implementations • 15 May 2024 • Anuj Sharma, Sukhdeep Singh, S Ratna
The chain code as feature extraction technique has shown significant results in literature and we have been able to use chain codes with graph neural networks.
no code implementations • 22 Apr 2024 • Lalita Kumari, Sukhdeep Singh, Vaibhav Varish Singh Rathore, Anuj Sharma
Thus, in this study, we present an end-to-end paragraph recognition system that incorporates internal line segmentation and gated convolutional layers based encoder.
no code implementations • 18 Apr 2024 • Mohammed Shaiqur Rahman, Ibne Farabi Shihab, Lynna Chu, Anuj Sharma
In this study, we introduce DeepLocalization, an innovative framework devised for the real-time localization of actions tailored explicitly for monitoring driver behavior.
no code implementations • 15 Apr 2024 • Shuo Wang, David C. Anastasiu, Zheng Tang, Ming-Ching Chang, Yue Yao, Liang Zheng, Mohammed Shaiqur Rahman, Meenakshi S. Arya, Anuj Sharma, Pranamesh Chakraborty, Sanjita Prajapati, Quan Kong, Norimasa Kobori, Munkhjargal Gochoo, Munkh-Erdene Otgonbold, Fady Alnajjar, Ganzorig Batnasan, Ping-Yang Chen, Jun-Wei Hsieh, Xunlei Wu, Sameer Satish Pusegaonkar, Yizhou Wang, Sujit Biswas, Rama Chellappa
The eighth AI City Challenge highlighted the convergence of computer vision and artificial intelligence in areas like retail, warehouse settings, and Intelligent Traffic Systems (ITS), presenting significant research opportunities.
no code implementations • 10 Apr 2024 • Sukhdeep Singh, Sudhir Rohilla, Anuj Sharma
This paper presents a survey on the existing studies of deep learning in handwriting recognition field.
no code implementations • 2 Apr 2024 • Ibne Farabi Shihab, Sudesh Ramesh Bhagat, Anuj Sharma
On the other hand, the ONE-PEACE LLM performed slightly better than the ensemble model in ideal scenarios but experienced a significant decline in performance under noisy conditions.
no code implementations • 22 Mar 2024 • Sukhdeep Singh, Anuj Sharma, Vinod Kumar Chauhan
Graph Neural Networks (GNN) have emerged as a popular and standard approach for learning from graph-structured data.
no code implementations • 22 Dec 2023 • James Gunn, Zygmunt Lenyk, Anuj Sharma, Andrea Donati, Alexandru Buburuzan, John Redford, Romain Mueller
Combining complementary sensor modalities is crucial to providing robust perception for safety-critical robotics applications such as autonomous driving (AD).
no code implementations • 3 Oct 2023 • Aparna Joshi, Jennifer Merickel, Cyrus V. Desouza, Matthew Rizzo, Pujitha Gunaratne, Anuj Sharma
Given the growing prevalence of diabetes, there has been significant interest in determining how diabetes affects instrumental daily functions, like driving.
1 code implementation • 16 Jun 2023 • Md Zahid Hasan, Jiajing Chen, Jiyang Wang, Mohammed Shaiqur Rahman, Ameya Joshi, Senem Velipasalar, Chinmay Hegde, Anuj Sharma, Soumik Sarkar
Our results show that this framework offers state-of-the-art performance on zero-shot transfer and video-based CLIP for predicting the driver's state on two public datasets.
no code implementations • 15 Apr 2023 • Milind Naphade, Shuo Wang, David C. Anastasiu, Zheng Tang, Ming-Ching Chang, Yue Yao, Liang Zheng, Mohammed Shaiqur Rahman, Meenakshi S. Arya, Anuj Sharma, Qi Feng, Vitaly Ablavsky, Stan Sclaroff, Pranamesh Chakraborty, Sanjita Prajapati, Alice Li, Shangru Li, Krishna Kunadharaju, Shenxin Jiang, Rama Chellappa
The AI City Challenge's seventh edition emphasizes two domains at the intersection of computer vision and artificial intelligence - retail business and Intelligent Traffic Systems (ITS) - that have considerable untapped potential.
no code implementations • 10 Nov 2022 • Armstrong Aboah, Yaw Adu-Gyamfi, Senem Velipasalar Gursoy, Jennifer Merickel, Matt Rizzo, Anuj Sharma
Previous approaches have treated vehicle maneuver detection as a classification problem, although both time series segmentation and classification are required since input telemetry data is continuous.
no code implementations • 11 Sep 2022 • Lalita Kumari, Sukhdeep Singh, VVS Rathore, Anuj Sharma
The handwritten text recognition problem is widely studied by the researchers of computer vision community due to its scope of improvement and applicability to daily lives, It is a sub-domain of pattern recognition.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
no code implementations • 20 Aug 2022 • Ujjwal Thakur, Anuj Sharma
Offline Handwritten Mathematical Expression Recognition (HMER) is a major area in the field of mathematical expression recognition.
no code implementations • 11 Jul 2022 • Lalita Kumari, Sukhdeep Singh, VVS Rathore, Anuj Sharma
In recent studies, combination of convolutional neural network and gated convolutional neural networks based models demonstrated less number of parameters in comparison to convolutional recurrent neural networks based models.
no code implementations • 23 May 2022 • Lalita Kumari, Sukhdeep Singh, Vaibhav Varish Singh Rathore, Anuj Sharma
In this study, an end-to-end paragraph recognition system is presented with a lexicon decoder as a post-processing step.
2 code implementations • 21 Apr 2022 • Milind Naphade, Shuo Wang, David C. Anastasiu, Zheng Tang, Ming-Ching Chang, Yue Yao, Liang Zheng, Mohammed Shaiqur Rahman, Archana Venkatachalapathy, Anuj Sharma, Qi Feng, Vitaly Ablavsky, Stan Sclaroff, Pranamesh Chakraborty, Alice Li, Shangru Li, Rama Chellappa
The four challenge tracks of the 2022 AI City Challenge received participation requests from 254 teams across 27 countries.
1 code implementation • 17 Apr 2022 • Mohammed Shaiqur Rahman, Jiyang Wang, Senem Velipasalar Gursoy, David Anastasiu, Shuo Wang, Anuj Sharma
This article presents a synthetic distracted driving (SynDD2 - a continuum of SynDD1) dataset for machine learning models to detect and analyze drivers' various distracted behavior and different gaze zones.
no code implementations • 2 Dec 2021 • Ujjwal Thakur, Anuj Sharma
In this paper, we have used the complete data instead of the sub-sampled methods that only handle partial data at a time.
no code implementations • 17 Nov 2021 • Udita Jana, Jyoti Prakash Das Karmakar, Pranamesh Chakraborty, Tingting Huang, Dave Ness, Duane Ritcher, Anuj Sharma
Movement specific vehicle classification and counting at traffic intersections is a crucial component for various traffic management activities.
1 code implementation • 15 Aug 2021 • Vinod Kumar Chauhan, Sukhdeep Singh, Anuj Sharma
To address these limitations, we have proposed a script independent deep learning network for HCR research, called HCR-Net, that sets a new research direction for the field.
1 code implementation • 25 Apr 2021 • Milind Naphade, Shuo Wang, David C. Anastasiu, Zheng Tang, Ming-Ching Chang, Xiaodong Yang, Yue Yao, Liang Zheng, Pranamesh Chakraborty, Christian E. Lopez, Anuj Sharma, Qi Feng, Vitaly Ablavsky, Stan Sclaroff
Track 3 addressed city-scale multi-target multi-camera vehicle tracking.
no code implementations • 14 Apr 2021 • Armstrong Aboah, Maged Shoman, Vishal Mandal, Sayedomidreza Davami, Yaw Adu-Gyamfi, Anuj Sharma
Our approach included creating a detection model, followed by anomaly detection and analysis.
no code implementations • 5 Apr 2021 • Atousa Zarindast, Jonathan Wood, Anuj Sharma
Recommender systems attempts to identify and recommend the most preferable item (product-service) to an individual user.
no code implementations • 16 Jan 2021 • Atousa Zarindast, Anuj Sharma
With the era of big data, an explosive amount of information is now available.
no code implementations • 5 May 2020 • Tongge Huang, Pranamesh Chakraborty, Anuj Sharma
This study shows that the proposed model can significantly improve the traffic data imputation accuracy in terms of Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) compared to state-of-the-art models on the benchmark dataset.
no code implementations • 30 Apr 2020 • Milind Naphade, Shuo Wang, David Anastasiu, Zheng Tang, Ming-Ching Chang, Xiaodong Yang, Liang Zheng, Anuj Sharma, Rama Chellappa, Pranamesh Chakraborty
Track 3 addressed city-scale multi-target multi-camera vehicle tracking.
no code implementations • 14 Nov 2019 • Kai Liang Tan, Subhadipto Poddar, Anuj Sharma, Soumik Sarkar
In this paper, we propose a DRL-based adaptive traffic signal control framework that explicitly considers realistic traffic scenarios, sensors, and physical constraints.
no code implementations • 31 May 2019 • Luis Riera, Koray Ozcan, Jennifer Merickel, Mathew Rizzo, Soumik Sarkar, Anuj Sharma
Among the several deep learning architectures, convolutional neural networks (CNNs) outperformed other machine learning models, especially for region proposal and object detection tasks.
1 code implementation • 20 Apr 2019 • Vinod Kumar Chauhan, Anuj Sharma, Kalpana Dahiya
LIBS2ML is a library based on scalable second order learning algorithms for solving large-scale problems, i. e., big data problems in machine learning.
no code implementations • 18 Apr 2019 • Saeed Arabi, Arya Haghighat, Anuj Sharma
This paper aims at providing researchers and engineering professionals with a practical and comprehensive deep learning based solution to detect construction equipment from the very first step of its development to the last one which is deployment.
no code implementations • 11 Apr 2019 • Charanjeet, Anuj Sharma
The large data is a challenge in Newton method to store second order matrices as hessian.
1 code implementation • 26 Dec 2018 • Vinod Kumar Chauhan, Anuj Sharma, Kalpana Dahiya
Nowadays stochastic approximation methods are one of the major research direction to deal with the large-scale machine learning problems.
no code implementations • NeurIPS 2018 • Anuj Sharma, Robert Johnson, Florian Engert, Scott Linderman
However, these sequences of swim bouts belie a set of discrete and continuous internal states, latent variables that are not captured by standard point process models.
no code implementations • 26 Oct 2018 • Charanjeet, Anuj Sharma
The results indicates that mistake rate reduces to zero or close to zero for various datasets and algorithms.
no code implementations • 24 Jul 2018 • Vinod Kumar Chauhan, Anuj Sharma, Kalpana Dahiya
Stochastic approximation is one of the effective approach to deal with the large-scale machine learning problems and the recent research has focused on reduction of variance, caused by the noisy approximations of the gradients.
no code implementations • 18 Jan 2018 • Vinod Kumar Chauhan, Anuj Sharma, Kalpana Dahiya
In this paper, we have proposed one possible solution to handle the big data problems in machine learning.
no code implementations • 16 Sep 2013 • Anuj sharma, Shubhamoy Dey
Feature selection is significant for sentiment analysis as the opinionated text may have high dimensions, which can adversely affect the performance of sentiment analysis classifier.
no code implementations • 16 Sep 2013 • Anuj Sharma, Shubhamoy Dey
This paper investigates the efficacy of different implementations of Self-Organizing Maps (SOM) for sentiment based visualization and classification of online reviews.
no code implementations • 16 Sep 2013 • Anuj Sharma, Dr. Prabin Kumar Panigrahi
As churn management is an important activity for companies to retain loyal customers, the ability to correctly predict customer churn is necessary.