Sökning: "Scene Classification"

Visar resultat 1 - 5 av 31 uppsatser innehållade orden Scene Classification.

  1. 1. Mutual Enhancement of Environment Recognition and Semantic Segmentation in Indoor Environment

    Master-uppsats,

    Författare :Venkata Vamsi Challa; [2024]
    Nyckelord :Semantic Segmentation; Scene Classification; Environment Recognition; Machine Learning; Deep Learning; Image Classification; Vision Transformers; SAM Segment Anything Model ; Image Segmentation; Contour-aware semantic segmentation;

    Sammanfattning : Background:The dynamic field of computer vision and artificial intelligence has continually evolved, pushing the boundaries in areas like semantic segmentation andenvironmental recognition, pivotal for indoor scene analysis. This research investigates the integration of these two technologies, examining their synergy and implicayions for enhancing indoor scene understanding. LÄS MER

  3. 2. Anomaly Detection with Machine Learning using CLIP in a Video Surveillance Context

    Master-uppsats, Linköpings universitet/Datorseende

    Författare :Christoffer Gärdin; [2023]
    Nyckelord :Datorseende; maskininlärning; CLIP; anomalidetektion; videoövervakning;

    Sammanfattning : This thesis explores the application of Contrastive Language-Image Pre-Training (CLIP), a vision-language model, in an automated video surveillance system for anomaly detection. The ability of CLIP to perform zero-shot learning, coupled with its robustness against minor image alterations due to its lack of reliance on pixel-level image analysis, makes it a suitable candidate for this application. LÄS MER

  4. 3. Trainable Region of Interest Prediction: Hard Attention Framework for Hardware-Efficient Event-Based Computer Vision Neural Networks on Neuromorphic Processors

    Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

    Författare :Cina Arjmand; [2023]
    Nyckelord :Artifical Intelligence; Machine Learning; Neuromorphic Engineering; Computer Vision; Technology and Engineering;

    Sammanfattning : Neuromorphic processors are a promising new type of hardware for optimizing neural network computation using biologically-inspired principles. They can effectively leverage information sparsity such as in images from event-based cameras, and are well-adapted to processing event-based data in an energy-efficient fashion. LÄS MER

  5. 4. A Study of Accumulation Times in Translation from Event Streams to Video for the Purpose of Lip Reading

    Kandidat-uppsats, KTH/Datavetenskap

    Författare :Didrik Munther; David Puustinen; [2022]
    Nyckelord :Lip-Reading; ANN; Event-based Cameras; Läppläsning; ANN; Eventbaserade kameror;

    Sammanfattning : Visually extracting textual context from lips consists of pattern matching which results in a frequent use of machine learning approaches for the task of classification. Previous research has consisted of mostly audiovisual (multi modal) approaches and conventional cameras. LÄS MER

  7. 5. DRIVING-SCENE IMAGE CLASSIFICATION USING DEEP LEARNING NETWORKS: YOLOV4 ALGORITHM

    Master-uppsats, Uppsala universitet/Statistiska institutionen

    Författare :Muhammad Tamjid Rahman; [2022]
    Nyckelord :Machine learning; Convolutional neural network; Object detection; YOLO;

    Sammanfattning : The objective of the thesis is to explore an approach of classifying and localizing different objects from driving-scene images using YOLOv4 algorithm trained on custom dataset.  YOLOv4, a one-stage object detection algorithm, aims to have better accuracy and speed. LÄS MER