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Python with AI tools course for job readiness in Hyderabad

Hyderabad: The Siasat’s Mahboob Hussain Jigar Career Guidance Centre has announced the beginning of free introductory classes ...
GitHub

Getting started with Ollama for Python

So far, running LLMs has required a large amount of computing resources, mainly GPUs. Running locally, a simple prompt with a typical LLM takes on an average Mac ...
IEEE

Hybrid-Fusion Mamba for Multitask Point Cloud Learning With Visual Perception Sensors

Abstract: Mobile robots and autonomous vehicles rely on 3-D point cloud technology for environmental perception, which often employ various visual perception sensors within their Internet of Things ...
IEEE

Weakly Supervised Learning for Point Cloud Semantic Segmentation With Dual Teacher

Abstract: Point cloud semantic segmentation has achieved considerable progress in the past decade. To alleviate expensive data annotation efforts, weakly supervised learning methods are preferable, ...
IEEE

Deep Learning Analysis of UAV Lidar Point Cloud for Individual Tree Detecting

Abstract: In this paper, we address the important task of Individual Tree Detection (ITD) in forest environments for enabling tree parameter estimation including tree count, height, volume, and crown ...
TechAnnouncer

Top 7 Free Coding Websites to Master Python in 2025

DataCamp is geared towards data science and analytics, offering specialized Python tracks with practical exercises using ...
IEEE

A 65 nm General-Purpose Compute-in-Memory Processor Supporting Both General Programming and Deep Learning Tasks

Abstract: This work presents a special unified compute-in-memory (CIM) processor supporting both general-purpose computing and deep neural network (DNN) operations, referred to as the general-purpose ...
IEEE

Clustering based Point Cloud Representation Learning for 3D Analysis

Abstract: Point cloud analysis (such as 3D segmentation and detection) is a challenging task, because of not only the irregular geometries of many millions of unordered points, but also the great ...
IEEE

Exploratory Learning in Engineering Programming

Abstract: This WIP paper presents new research on exploratory learning, an educational technique that reverses the order of standard lecture-based instruction techniques. In exploratory learning, ...
IEEE

Contextual Sequence-to-Point Deep Learning for Household Energy Disaggregation

Abstract: This paper examines a contextual paradigm for energy disaggregation using Non-Intrusive Load Monitoring (NILM). Due to numerous issues including low sampling rates, missing data, misaligned ...
IEEE

Deep Scene Flow Learning: From 2D Images to 3D Point Clouds

Abstract: Scene flow describes the 3D motion in a scene. It can be modeled as a single task or as a composite of the auxiliary tasks of depth, camera motion, and optical flow estimation. Deep learning ...
IEEE

An Improved Sequence-to-Point Learning for Non-Intrusive Load Monitoring Based on Discrete Wavelet Transform

Abstract: Nonintrusive load monitoring (NILM) is a process that monitors the aggregated power consumption data of customers measured by a single sensor and decomposes the real-time power consumption ...