image recognition thesis

Oulu University of Applied Sciences Information Technology, Internet Services. Author: Hung Dao Title of the bachelor's thesis: Image Classification Using Convolutional Neural Networks Supervisor: Jukka Jauhiainen Term and year of completion: Spring 2020 Number of pages: 31. The objective of this thesis was to study the application of deep ...

Master's thesis, Department of Computer Science, Univer-sity of Toronto, 2009. ... [Show full abstract] image recognition technology based on depth learning, including the design ideas ...

This thesis was motivated by the challenge of choosing the right CNN architecture and training technique for image recognition tasks, especially when dealing with large datasets.

The Repository at St. Cloud State. Culminating Projects in Computer Science and Information Technology Department of Computer Science and Information Technology 5-2021. Object Detection and Recognition Using YOLO: Detect and Recognize URL(s) in an Image Scene. John Ajala. St. Cloud State University Follow this and additional works at: https ...

Deep learning algorithms, such as those used for image recognition, holds promise for automated medical diagnosis and in guiding clinical decision-making. At the same time, there remain several important challenges to the development and clinical translation of medical deep learning systems. ... This thesis demonstrates the potential of deep ...

This thesis aims to identify the most effective approach for image recognition by comparing different CNN architectures and training techniques. The literature review provides an overview of CNNs for image recognition, discussing various architectures and training techniques that have been used in previous studies. The review explains common ...

Abstract: With the development of machine learning for decades, there are still many problems unsolved, such as image recognition and location detection, image classification, image generation, speech recognition, natural language processing and so on. In the field of deep learning research, the research on image classification has always been the most basic, traditional and urgent research ...

The goal of our research is to develop methods advancing automatic visual recognition. In order to predict the unique or multiple labels associated to an image, we study different kind of Deep Neural Networks architectures and methods for supervised features learning. We first draw up a state-of-the-art review of the Convolutional Neural Networks aiming to understand the history behind this ...

Image Processing, Machine Learning and Visualization for Tissue Analysis LESLIE SOLORZANO ISSN 1651-6214 ISBN 978-91-513-1173-9 ... This thesis is the summary of an interdisciplinary work with the goal of helping researchers in the medical and biological fields to answer questions

Abstract. Image restoration and classification is a classical problem of image processing, computer vision and machine learning. In recent times, with the increase of Artificial Neural Network ...

Fast and Accurate Image Recognition. Thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering by Research by Sri Aurobindo Munagala 201402160. [email protected]. International Institute of Information Technology Hyderabad - 500 032, INDIA January 2022.

In general, we learn image representations via a supervised metric-based approach with siamese neural networks, then reuse that network's features for one-shot learning without any retraining. In our experiments, we restrict our attention to character recognition, although the basic approach can be replicated for almost any modality (Figure 2).

Table 5, model order of 2 means that if an image is partitioned into 2 segments only, the. recognition accuracy is 16%. Model order of 3 implies that if an image is partitioned into 3. segments plus the 2 segments of model order 2, than an accuracy of 16% is achieved.

This thesis has specifically targeted on the issue of image recognition so that we may easily find desired object from any kind of classified image. 12 1.3 Thesis Outline The thesis is ordered as follows: Chapter 1 is the discussion of proper prologue of the thesis which includes our inspiration for starting this thesis and goals and objectives ...

The system is implemented in Symbian C++ on a Nokia N95 phone and detects zebra crossings in real time (3 frames per seconds), using the phone's video capturing mode. The user points the camera in the estimated direction and the application outputs an acoustic notifier if a zebra crossing is detected.

Food image recognition plays an important role in healthcare applications that monitor eating habits, dietary, nutrition, etc. Therefore, different deep learning approaches are proposed to address food image recognition. This dissertation presents three methods to deal with several challenges in recognizing food images.

The collection of information about buildings and their colors is an important aspect of urban planning. The intelligent recognition of buildings using image information plays a significant role in the development of smart cities and urban planning. This thesis proposes a building color-recognition technique based on morphological features utilizing convolutional neural networks and the K ...

Automated dataset generation for image recognition using the example of taxonomy. Jaro Milan Zink. This master thesis addresses the subject of automatically generating a dataset for image recognition, which takes a lot of time when being done manually. As the thesis was written with motivation from the context of the biodiversity workgroup at ...

The image classification is a classical problem of image processing, computer vision and machine learning fields. In this paper we study the image classification using deep learning.

In recent years, deep convolution neural network has exhibited excellent performance in computer vision and has a far-reaching impact. Traditional plant taxonomic identification requires high expertise, which is time-consuming. Most nature reserves have problems such as incomplete species surveys, inaccurate taxonomic identification, and untimely updating of status data. Simple and accurate ...

There are various good thesis topics in digital image processing for masters as well as for Ph.D. Find the list of thesis and research topics here. ... Recognition involves assigning of a label, such as, "vehicle" to an object completely based on its descriptors. It is a method of recognising a specific object in an image or video.

2.1 Overview of Image Recognition Image processing and image recognition play important role in classical computer vision theory. In classical computing theory, we store the image in computers, apply machine learning algorithms, and let the computer recognize the image. In the first step, images are stored as pixel values in classical computers ...

This work proposes a recurrent neural network based method to recognize Amharic text-line images and uses Long Short Term Memory (LSTM) networks together with CTC (Connectionist Temporal Classification). This paper introduces a dataset for an exotic, but very interesting script, Amharic. Amharic follows a unique syllabic writing system which uses 33 consonant characters with their 7 vowels ...