الصفحة 1
الصفحة 1
News bot
The process of gathering and organizing news content has become a challenging task for emerging news sites, necessitating the employment of highly experienced personnel with specialized skills in the field. However, recent advancements in artificial intelligence technology have led to the development of news bots that can efficiently fetch, classify, and rephrase news content from various sources, enabling users to access the latest and well-formulated news without the need for RSS (Really Simple Syndication).
Introduction to Machine Learning with Applications in Information Security
Provides a classroom-tested introduction to a wide variety of machine learning and deep learning algorithms and techniques, reinforced via realistic applications. The book is accessible and doesn't prove theorems, or dwell on mathematical theory. The goal is to present topics at an intuitive level, with just enough detail to clarify the underlying concepts. The book covers core classic machine learning topics in depth, including Hidden Markov Models (HMM), Support Vector Machines (SVM), and clustering. Additional machine learning topics include k-Nearest Neighbor (k-NN), boosting, Random Forests, and Linear Discriminant Analysis (LDA). The fundamental deep learning topics of backpropagation, Convolutional Neural Networks (CNN), Multilayer Perceptrons (MLP), and Recurrent Neural Networks (RNN) are covered in depth. A broad range of advanced deep learning architectures are also presented, including Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), Extreme Learning Machines (ELM), Residual Networks (ResNet), Deep Belief Networks (DBN), Bidirectional Encoder Representations from Transformers (BERT), and Word2Vec.
Intelligent cryptocurrency trading assistant
With blockchain being invented in 2008, cryptocurrencies have grown steadily through the years. Cryptocurrencies continue today to be an extremely interesting phenomenon. Having quickly achieved popularity and becoming very popular, cryptocurrencies continue to be a profitable investment tool, capable of generating huge profits on exchanges and transactions. Being a professional trader is not an easy task to achieve, a professional trader needs to observe and process multiple factors and events that affect the cryptocurrency market to make the right decision. What makes this process challenging is that some of the factors cannot be predicted or calculated but rather, their changes should be observed and comprehended, and an action should be taken in response quickly in order to maximize the profit or minimize the loss.
Instrumaster
Experiments with different neural network structures and algorithms in order to achieve musical note recognition as well as musical instrument recognition, all bundled in a mobile application. It also aims to create the most effective music-learning application that works completely offline, which is hard to find in modern music applications. The paper also explores why the instrument identifying AI is solely based on Multi-Layer Perceptron (MLP) and why the note-identifying AI system was chosen to be a ML system over CNN or other deep-learning trained AI. The paper presents feature extraction methods for audio signals and files and dives deep into the process, such as FFT, MFCCs, Wavelengths, sampling rates, etc. It also touches on Logistic Regression Algorithms, their limitations, and their performance with the different use cases in the application. All these techniques are then compared side by side for maximally added value, making this research paper a good reference for any future developers looking to find optimal neural networks techniques when it comes to audio processing and analysis.
Image Processing Using Pulse-Coupled Neural Networks
This is the first book to explain and demonstrate the tremendous ability of Pulse-Coupled Neural Networks (PCNNs) when applied to the field of image processing. PCNNs and their derivatives are biologically inspired models that are powerful tools for extracting texture, segments, and edges from images.
Hearing faces
Our project aims to aid deaf-mute people by tracking hand movements of the deaf-mute person for word level American Sign Language using WLASL model that include 2D CNN -3D CNN and RNN networks training on WLASL large video dataset, then generating the corresponding text and analyzing the person's facial gestures to generate information related to the tone of voice that is most appropriate to the person's age, gender, and race through MTCNN network algorithm that training on generated dataset by us depending on blending VOXCELEB dataset and VGGFACE dataset .
Elevating video content creation with ai assistance = ارتقاء إنشاء محتوى الفيديو بمساعدة الذكاء الاصطناعي
We developed an AI Assistant equipped with features such as description crafting, title generation, keyword extraction, image captioning, clickbait detection, and sentiment analysis.To achieve these functionalities, we proposed a model for generating video descriptions using ResNet50 as a feature extractor and a LSTM network with an attention mechanism as a sequence generator, achieving a BLEU-1 score of 0.907 and a ROUGE-L score of 0.645. For keyword extraction, we utilized Sentence Transformer to identify strategically relevant keywords from the generated descriptions. For title generation, we fine-tuned the BART model, achieving a ROUGE-L score of 0.45. For clickbait detection, we used SVC classifier with linear kernel and TF-IDF vectorization for feature extraction, resulting in 96% accuracy. Our sentiment analysis model using a CNN-LSTM architecture achieved 80% accuracy in analyzing comments on videos. For image captioning, we employed a feature extractor with a CNN layer followed by an LSTM model, achieving a BLEU-1 score of 0.53. Our platform empowers creators by simplifying complex tasks and offering deeper audience engagement insights, making it a powerful tool in the evolving digital content creation.
Deepfake detection
The rise of large language models (LLMs) and the increasing sophistication of deepfake images have made detecting synthetic content a pressing challenge. Several approaches have been proposed to tackle this problem, including statistical analysis, and machine learning algorithms. In this project, A novel zero-shot approach is proposed that utilizes the power of LLMs to detect fake text. The pre-trained LLM is fine-tuned to enhance its ability to differentiate real and fake text. The approach uses the LLM to detect text by analyzing the log probabilities of the text. For detecting fake images, computer vision algorithms and neural networks are used to analyze facial features. The facial region is cropped and preprocessed and the neural network identifies patterns indicative of synthetic content.
Deep Learning with PyTorch Lightning : Build and train high-performance artificial intelligence and self-supervised models using Python
You’ll learn how to configure PyTorch Lightning on a cloud platform, understand the architectural components, and explore how they are configured to build various industry solutions. You’ll build a neural network architecture, deploy an application from scratch, and see how you can expand it based on your specific needs, beyond what the framework can provide. In the later chapters, you’ll also learn how to implement capabilities to build and train various models like Convolutional Neural Nets (CNN), Natural Language Processing (NLP), Time Series, Self-Supervised Learning, Semi-Supervised Learning, Generative Adversarial Network (GAN) using PyTorch Lightning.
Data mining : Concepts, models, methods, and algorithms ; 3rd ed.
Presents the latest techniques for analyzing and extracting information from large amounts of data in high-dimensional data spaces. Explores big data and cloud computing Examines deep learning Includes information on convolutional neural networks (CNN) Offers reinforcement learning Contains semi-supervised learning and S3VM Reviews model evaluation for unbalanced data
Content based social platform optimization “Fashion Platform"
The purpose of this project is to design a platform that concentrates on Fashion in addition to assisting users with gathering an informative feedback, as well as linking local stores to those users. This platform will be delivered as a mobile application that is available to any user who is interested in expressing and sharing his/her prevailing taste in fashion simply by posting photos, interacting with other people’s posts and leaving comments for them. The app will also provide some features in an attempt to push the users to be more enthusiastic and to be more encouraged about trying and continuously using this app. Moreover, this platform will incorporate a Shop section, which will be the actual local stores that are connected to it, so the user can buy an item that he/she is fond of.
Clear Blogging : How People Blogging Are Changing the World and How You Can Join Them
Clear Blogging sets out to answer in non-technical terms what blogging has to offer, and why and how you should blog. Clear Blogging will show you why blogging has shaken up mainstream media, and how a blogger can end up on CNN.
Blind smart helmet
The Smart Helmet for the Blind is a project aimed at providing solutions for the challenges faced by blind individuals in their daily lives. The problem of detecting objects, identifying obstacles and distances, knowing the current location, and using a mobile application is a common issue for blind people. To address these problems, the Smart Helmet project was created, utilizing advanced technology and artificial intelligence to provide real-time assistance to the wearer. The helmet is connected to a Raspberry Pi 4, which processes information from the helmet's cameras and AI algorithms to analyze and predict the surrounding environment for a blind person.
Artificial intelligence hardware design : Challenges and solutions
Learn foundational and advanced topics in Neural Processing Unit design with real-world examples from leading voices in the field. A thorough introduction to neural networks and neural network development history, as well as Convolutional Neural Network (CNN) models Explorations of various parallel architectures, including the Intel CPU, Nvidia GPU, Google TPU, and Microsoft NPU, emphasizing hardware and software integration for performance improvement Discussions of streaming graph for massive parallel computation with the Blaize GSP and Graphcore IPU An examination of how to optimize convolution with UCLA Deep Convolutional Neural Network accelerator filter decomposition
AI sign language translator
People with disabilities are facing a lot of difficulties every day. Whether it is in social life, work or education environment, or in communication. The effect of assistive technologies in enhancing people with disabilities was huge. Assistive technologies refer to the term of products or related systems that are used to help people with disabilities to maintain or improve functioning and thereby promote well-being. These technologies allow people with difficulties to be more productive in life. Assistive technologies could be in many forms such as wheelchairs, communication products or other forms. In the communication products, many efforts have been made to develop systems or devices that assist individuals who have difficulty understanding and producing speech.
