Author: Aneesh Tickoo

Aneesh Tickoo
463 POSTS0 COMMENTS
Aneesh Tickoo is a consulting intern at MarktechPost. He is currently pursuing his undergraduate degree in Data Science and Artificial Intelligence from the Indian Institute of Technology(IIT), Bhilai. He spends most of his time working on projects aimed at harnessing the power of machine learning. His research interest is image processing and is passionate about building solutions around it. He loves to connect with people and collaborate on interesting projects.

Researchers Propose Neural Density-Distance Field (NeDDF), a Distance Field Representation that is Reciprocally Constrained to the Density Field

Recent research has focused on employing coordinate-based neural networks, commonly referred to as neural fields, to represent 3D forms as an alternative to point...

Apple AI Researchers Propose GAUDI: a Generative Model That Captures Distributions of Complex and Realistic 3D Scenes

Progress in 3D generative models is desperately needed if learning systems are to comprehend and build 3D spaces. The researchers honor Antoni Gaud, whose...

Researchers at Meta AI Create ‘OMNI3D’ Dataset For Object Recognition And ‘Cube R-CNN’ Model That Generalizes To Unseen Images

Computer vision has long struggled to comprehend objects and their characteristics from a single image, a topic that has applications in robotics, assistive technology,...

Researchers at Graz University of Technology Develop AdaNeRF: Adaptive Sampling for Real-time Rendering of Neural Radiance Fields Directly from Sparse Observations

The development of neural radiance fields improved state-of-the-art applications, including 3D reconstruction, rendering, animation, and scene relighting, pushing the limits of contemporary computer graphics...

Allen Institute for AI Researchers Propose PROCTHOR: A Machine Learning Framework for Procedural Generation of Embodied AI Environments

Using large-scale training data, computer vision, and natural language processing models have strengthened. Recent models like CLIP, DALL-E, GPT-3, and Flamingo leverage vast quantities...

University of Illinois Researchers Develop XMem; A Long-Term Video Object Segmentation Architecture Inspired By Atkinson-Shiffrin Memory Model

Video object segmentation (VOS) identifies and highlights certain target items in a video. Most VOS techniques use a feature memory to store relevant deep-net...

Apple Researchers Developed an Adaptive Bayesian Learning Agent That Employs a Novel Form of Dynamic Memory for Interpretable Sequential Optimisation

The practice of gradually learning from data to make better judgments over time is known as sequential optimization. It is frequently phrased in the...

In A Latest Computer Vision Paper, Researchers Propose A Novel Framework To Leverage The Representation And Generalization Capability Of Pre-Trained Multi-Modal Models Towards Improved...

Open Vocabulary Detection attempts to generalize beyond the restricted number of base classes designated during the training phase. At inference, the objective is to...

AI Researchers From Taiwan Develop YOLO-v7, Which Sets New State of The Art For Real-Time Object Detectors

Real-time object identification is a critical issue in computer vision since it is frequently required in computer vision systems, including multi-object tracking, autonomous driving,...

AI Researchers From Korea Introduce ‘DailyTalk’, A High-Quality Conversational Speech Dataset Designed For Text-To-Speech

The most important thing for a Text-to-Speech TTS system is to save and communicate the context of the present discourse. Current TTS models have...

AI Researchers Develop A Computer Vision Method For Highly Accurate Dichotomous Image Segmentation

Since many years ago, computer vision datasets that are the basis for many Artificial Intelligence (AI) models have provided accurate annotations. They have been...

AI Researchers at Amazon Develop a Novel Technique by Training a Neural Network to Have Better Joint Representations of Image and Text

Joint image-text embedding is the foundation of most Vision-and-Language (V+L) tasks, where multimodality inputs are simultaneously processed for combined visual and textual understanding. It...

🐝 🐝 Join the Fastest Growing AI Research Newsletter...

X