Browsing by Author "Shaikh, Abdus Salam"

Now showing 1 - 7 of 7
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    Augmented reality for educational enhancement
    (AIKTC, 2017-05) Panwala, Sameer; Shaikh, Abdus Salam; Ghare, Abdullah (13CO29); Kazi, Shadab (13CO34); Khan, Mohammed (13CO38); Rangwala, Mustafa (13CO52)
    Augmented Reality superimposes virtual objects over real world environment. Educators know that learning deepens, not just through reading and listening, but also through creating and interacting. This proposed project of ours aims to enhance current educational system using Augmented Reality. We are developing an application which will show animations, videos and 3D models of educational material. This project can enhance learning, creativity and retention among students. Our application will also foster intellectual curiosity among students making them smarter. We aim to change the conventional way of education and open a new opportunity towards a smart classroom.
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    Automated diet planner
    (AIKTC, 2019) Shaikh, Abdus Salam; Malbari, Sabiya Abdul Rashid (15CO06); Shaikh, Mariya Irfan Ahmed (14CO07); Alekar, Ifat Salim (15CO02)
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    Emomusic: An emotion based music player
    (AIKTC, 2020-05) Shaikh, Abdus Salam; Rawal, Hasib Ibrahim (16CO45); Mohd Zeeshan, Mohd Abbas (16CO41); Khan, Zeeshan Kadeer (16CO33)
    When we talk about the human emotion the human face act as a very important in terms of finding an individual’s mood or emotion. There are various emotions such as happy, sad, angry, etc which can be identified with help of facial expressions. till now if the user wants to make the playlist they have to go through the list of the music then select the songs based on their emotions but it takes consumes more time and it becomes a very tedious and upheld task for the user. Previously many algorithms have been proposed for generating the songs automatically. but the conventional algorithms which are in use are required various external hardware or sensors like electroencephalogram for capturing and identifying the human emotion via human brain it makes the complete process very slow and less accurate. existing systems are not user-friendly they have the complex architecture however This proposed system based on extracted facial expression is user-friendly any user can use it anywhere any time. also proposed system eliminate the task of manually creating the playlists of songs based on the emotions it automatically generates the different playlist It saves much more time and efforts of users who are music lover. Thus the proposed system (Emo-music) aims to minimize the computational time as compared to existing algorithms for getting the results it also reduces the overall cost of the designed system, thereby given features will automatically increase the overall accuracy of the proposed system. The proposed system (Emo-music) tested on both utilize-dependent and utilize-independent datasets. Visages are captured utilizing an inbuilt camera. The precision or Accuracy of the emotion detection algorithm utilized in the system is around 80-95%. Thus, it yields better precision compared to the algorithms utilized in the literature survey. Keywords: Android,Human Face, Emotional Features, PlayList ,User Independent Dataset,User Dependent Dataset, Emotion detection, Inbuilt Camera,Emotion Recognition , Face Recognition,Songsextraction,web scrapping,youtube-dl.
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    Online grocery delivery system
    (AIKTC, 2020-05) Shaikh, Abdus Salam; Ansari, Nooras Fatima Mohammed Hashim (16CO01); Sarang, Amina Sharif (16CO08); Shaikh, Mariyam Anis (16CO12)
    Online shopping has become a trend in all the sectors of life. As businesses are expanding, it is important for businesses to understand the consumer’s behaviour. The style of grocery shopping such as online grocery shopping made by retailers to attract customers. It is a technology which is popular mostly in big and metropolitan cities of India. We aim to provide techniques which can help the customers by spending less time on paying for products by customizing their experience of shopping and analyzing their feelings towards the shops of their choice. This system has three modules: Customer, Shopkeeper and Delivery Boy. This System focuses on building a website which can make the online grocery shopping a lot easier for customers. This automated system provides many functionalities which will make it better than the previous systems available. The facilities provided will be–registering, signing in, searching, viewing recommended products based on different categories, reviewing the products according to your experience and ordering the grocery items with secured online transaction. It is a beneficial system for small retailers to expand their business as they can directly deliver the products to the customers in less time. Voice to text, smart list are some add-on features new for an online grocery store. Not only this customer can also track products. A smart list is a list of products based on previous history of frequently bought products Keywords: Machine Learning, Natural language Processing (NLP), Text Analysis, Speech Recognition, Product Recommendations, Artificial intelligence.
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    SignTalk and animator for speech and hearing imapaired
    (AIKTC, 2017-05) Khan, Mubashir; Shaikh, Abdus Salam; Shaikh, Ruba (13CO12); Siddiqui, Sayma (13CO14); Biya, Haseeb (13CO21); Khot, Sufiyan (12CO41)
    Communication is basic fundamental human right, however who are deaf and mute communicate differently than everyone else using Sign Language (SL), while we communicate verbally. This puts them at disadvantage. Our system will help them better communicate with rest of the world without changing how they already interact with each other. The system, SignTalk i.e. Hand gloves will translate sign language to voice. Flex sensors, accelerometer, gyroscope, are placed on hand gloves to capture hand movements. Arduino Nano recognizes these signals and sends it to smart phone via Bluetooth for voice generation. Animator is an android application that takes text sentences as input and converts it to 2D animations for facilitating two way communication.
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    Smart healt disease prediction system
    (AIKTC, 2021-05) Shaikh, Abdus Salam; Shaikh, Faiyyaz Tanvir (17CO45); Shaikh, Soaib Riyaz (17CO48); Shaikh, Ubed Ikram (17CO49); Nivekar, Bilal Hamza (16DCO66)
    We are living in an era where technology is advancing at unprecedented rate. Nowadays, Artificial Intelligence and Machine Learning are used in every domain wherein machines or computers are being trained to work automatically with very less human efforts. Machine Learning Algorithms are very useful in prediction, analysis and training. We will use ML Algorithms in predicting and analysis of various diseases in human beings. Health is one of the precious asset for a human being but due to the ongoing pandemic people can’t recognize and treat their diseases from their home so we are aiming to develop a disease prediction system using ML Algorithms for better prediction of diseases by providing their symptoms to recognize the diseases more precisely with its consequences and treatment with the ease of using it at their own comfort zone. We are developing this system also because people can consult with their respective doctors via live consultation without physical contact. Our interface would help people to some extent in-order to reduce the risk associated with predicted diseases to reduce the impact on other body parts. With the help of extensive powerful ML Algorithms accuracy is highest. People can also maintain safety protocols in this pandemic by predicting the diseases from their home. Keywords: Scikit-learn, NumPy, Data Preprocessing, Dataset, Algorithms, Training Data, Training Set, Machine Learning, Naive Bayes, KNN, Decision Tree, Kernel SVM, Logistic Regression, Random Forest, Django, Training Model,Web Module, Data Collection Module, APIs, Artificial Intelligence, Disease Detection Module, Authentication, User Interface, SHDPS.
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    Tour buddy (monument detection using yolo)
    (AIKTC, 2021-05) Shaikh, Abdus Salam; Khan, Sahijad Ali Sayyed Ali (18DCO06); Khan, Zaid Mehmood (18DCO07); Siddiqui, Saif Shamshad (15CO40); Natiq, Abis Husain Parvez (18DCO12)
    In this paper, we have classified the famous Indian Monuments as India is 7th largest country which has large number of monuments and Historic places where millions of tourists are visits everyday but it is not possible everyone knows everything about those monuments.The paper proposes an approach for classification of various monuments based on the features of the monument images .A well known Convolutional neural network (CNN) Algorithm and YOLO has been adopted to provide on-time and striking accuracies for classifying the Monument images.The Darknet library YOLO has been used for all the training computations as YOLO is a clever convolutional neural network (CNN) for doing object recognition in realtime. The algorithm applies a single neural network to the full image, and then divides the image into multiple regions and predicts bounding boxes and probabilities for each region.After the models gets trained the overall accuracy achieved is 98,Using CNN and YOLO , for a total 20 different monuments that have been considered in the dataset for classifications. Index Terms—YOLO, Convolutional Neural Network ,Deep Learning, Machine Learning , Image recognition .