The Cosmic Ray Observatory Project (CROP) is a statewide education and research experiment involving Nebraska high school students, teachers and university undergraduates in the study of extensive cosmic-ray air showers. A network of high school te...
Deep Neural Networks can generalize despite being significantly overparametrized. Recent research has tried to examine this phenomenon from various view points and to provide bounds on the generalization error or measures predictive of the generaliza...
Social sciences have an important challenge today to take advantage of new research opportunities provided by large amounts of data generated by online social networks. Because of its marketing value, sports clubs are also motivated in creating and m...
Deep Reinforcement Learning (DRL) has been successfully applied in several research domains such as robot navigation and automated video game playing. However, these methods require excessive computation and interaction with the environment, so enhan...
For decades, the Controller Area Network (CAN) has served as the primary in-vehicle bus (IVB) and extended its use to many non-vehicular systems. Over the past years, CAN security has been intensively scrutinized, yielding extensive research literatu...
The latest advances in deep learning have facilitated the development of highly accurate monocular depth estimation models. However, when training a monocular depth estimation network, practitioners and researchers have observed not a number (NaN) lo...
Litmaps changes the way researchers search for papers and conduct literature reviews. Using the citation network and advanced search features, Litmaps help you find the most important papers on …
The proliferation of smart home devices has created new opportunities for empirical research in ubiquitous computing, ranging from security and privacy to personal health. Yet, data from smart home deployments are hard to come by, and existing empiri...
Studies of virtual try-on (VITON) have been shown their effectiveness in utilizing the generative neural network for virtually exploring fashion products, and some of recent researches of VITON attempted to synthesize human image wearing given multip...
The TV is dead motto of just a few years ago has been replaced by the prospect of Internet Protocol (IP) television experiences over converged networks to become one of the great technology opportunities in the next few years. As an introduction to t...
The 3D incompressible Navier-Stokes equations model essential fluid phenomena, including turbulence and aerodynamics, but are challenging to solve due to nonlinearity and limited solution regularity. Despite extensive research, the full mathematical...
Jul 23, 2024 · MAIA is a multimodal agent for neural network interpretability tasks developed at MIT CSAIL. It uses a vision-language model as a backbone and equips it with tools for experimenting on …
**Reference**: Full credit to Larry Smith that covered this back in 2019. I will summarise the key points from my research into this. **Introduction** As we know the DTCC was set-up to take advanta...
The research introduces a novel plant disease detection model based on Convolutional Neural Networks (CNN) for plant image classification, marking a significant contribution to image categorization. The innovative training approach enables a streamli...
Making accurate motion prediction of surrounding agents such as pedestrians and vehicles is a critical task when robots are trying to perform autonomous navigation tasks. Recent research on multi-modal trajectory prediction, including regression and...
In this paper of a research based project, using Bidirectional Long Short-Term Memory (BiLSTM) networks, we provide a novel Fight Scene Detection (FSD) model which can be used for Movie Highlight Generation Systems (MHGS) based on deep learning and N...
Person re-identification (re-ID) aims to recognize a person-of-interest across different cameras with notable appearance variance. Existing research works focused on the capability and robustness of visual representation. In this paper, instead, we p...
Stock price prediction is a challenging problem in the field of finance and receives widespread attention. In recent years, with the rapid development of technologies such as deep learning and graph neural networks, more research methods have begun t...
In this research endeavor, it was hypothesized that the sound produced by animals during their vocalizations can be used as identifiers of the animal breed or species even if they sound the same to unaided human ear. To test this hypothesis, three ar...
This paper is an extension of our previous conference paper. In recent years, there has been a growing interest among researchers in developing and improving speech recognition systems to facilitate and enhance human-computer interaction. Today, Auto...