IIIT-Delhi Institutional Repository

Browsing by Subject "Machine learning"

Browsing by Subject "Machine learning"

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  • Aerial pedestrian detection using vision based approach 
    Chaudhuri, Yashwardhan; Buduru, Arun Balaji (Advisor) (IIIT-Delhi, 2022-12)
    Aerial object detection is becoming increasingly popular since images with a large field of view provide higher information per pixel than images with a short field of view. It is popularly used for pedestrian detection ...
  • Artificial intelligence based models for predicting head and neck cancer from genomics data of single cells 
    Jarwal, Akanksha; Raghava, Gajendra Pal Singh (Advisor) (IIIT-Delhi, 2023-02)
    Head and Neck Squamous Cell Carcinoma (HNSC) or Head and Neck Cancer is the sixth most highly prevalent cancer type worldwide. Early detection of HNSC is one of the important challenges in managing the treatment of cancer ...
  • Artificial intelligence in healthcare 
    Kashyap, Ritwik; Sethi, Tavpritesh (Advisor) (IIIT-Delhi, 2023-11-29)
    In the realm of critical care medicine, the continuous generation of vital signs time series data from Intensive Care Units (ICUs) serves as a pivotal element for clinicians in evaluating patient prognostics and accessing ...
  • Assessment of data-driven and deterministic approaches for predicting bace-1 inhibitor binding affinities 
    S, Amaithi Priya; Murugan, N Arul (Advisor) (IIIT-Delhi, 2022-06)
    BACE1 (beta-site amyloid precursor protein cleaving enzyme 1) is an aspartyl protease with a transmembrane domain that cleaves at the 671st position of amyloid precursor protein (APP) at the beta site. The production and ...
  • Capturing mannerisms in speech data 
    Nambiar, Pranav; Arora, Chetan (Advisor); Anand, Saket (Advisor) (IIITD-Delhi, 2018-04-30)
    Text-to-speech systems generally require large amounts of annotated speech data with the quality of both the annotations and speech being a huge factor. As a result, most of the research performed has been on highly curated ...
  • Co-Designing CNN & FPGA architectures using compression techniques for classifi cation & detection networks. 
    Goel, Pulkit; Anand, Saket (Advisor); Fell, Alexander (Advisor) (IIITD-Delhi, 2019-04-28)
    Deep learning neural networks have revolutionized the elds of Computer Vision, Robotics, Artifi cial Intelligence. However, these State of the art algorithms come at a high computational cost, huge memory requirements and ...
  • Deep learning based multitask learning for first-person videos 
    Gupta, Divam; Arora, Chetan (Advisor) (IIIT-Delhi, 2016-07-18)
    First person videos captured from wearable cameras are growing in popularity.Standard algo- rithms developed for third person videos often do not work for such egocentric videos because of drastic change in camera ...
  • Detecting cows and dogs on delhi streets 
    Saurav, Sakti; Arora, Chetan (Advisor) (IIIT-Delhi, 2016-11-17)
    Did you know that India is now the home to world's largest number of blind people? 41% of the blind population are from India. And one of the real security concerns of visually impaired persons is that whether they get ...
  • Detecting gait abnormalities using 3D pose estimation 
    Khan, Aman; Jerripothula, Koteswar Rao (Advisor) (2022-12)
    The pattern of a person’s limbic movements and behavioral tendencies during locomotion is well-known as a person’s gait, which can get affected due to a medical condition. Persons suffering from neurological disorders often ...
  • Development of in silico models for predicting Alzheimer’s disease from single cell genomics 
    Srivastava, Aman; Raghava, Gajendra Pal Singh (Advisor) (IIIT-Delhi, 2023-02)
    Alzheimer’s disease is progressing as the most prevalent neurological disorder world- wide. It is the most common cause of dementia in ageing society. An artificial Neural Network (ANN) is a set of neural networks which ...
  • Digital forensics 2.0: an automated, efficient, and privacy preserving digital forensic investigation framework 
    Verma, Robin; Gupta, Gaurav (Advisor); Chang, Donghoon (Advisor) (IIIT-Delhi, 2018-05)
    The current state of digital forensic investigation is continuously challenged by the rapid technological changes, the increase in the use of digital devices (both the heterogeneity and the count), and the sheer volume of ...
  • Learning algorithms for micro-doppler radar based detection, classification and imaging of humans in indoor environments 
    Vishwakarma, Shelly; Ram, Shobha Sundar (Advisor) (IIIT-Delhi, 2020-02)
    Indoor radars have been researched and developed to detect and monitor humans for applications that range from law enforcement, security and surveillance purposes to ubiquitous sensing applications such as smart home or ...
  • Machine learning in cancer genomics 
    Gupta, Taejas; Gupta, Anubha (Advisor) (IIITD-Delhi, 2019-04-28)
    Cancer is caused by an increased amount of cell growth in an area due to alterations in protein synthesis caused by mutations in certain genes known as cancer driver genes. Determining the gene regulatory network for the ...
  • Me, myself and my killfie: characterizing and preventing selfie deaths 
    Vachher, Mayank; Kumaraguru, Ponnurangam (Advisor) (2016-11-16)
    Over the past couple of years, clicking and posting selfies has become a popular trend. However, since March 2014, 127 people have died and many have been injured while trying to click a selfie. Researchers have studied ...
  • Multiple myeloma cancer cell instance segmentation. 
    Sagar, Dikshant; Gupta, Anubha (Advisor); Goswami, Shubham (Advisor) (IIIT- Delhi, 2021-05)
    Images remain the largest data source in the field of healthcare. But at the same time, they are the most difficult to analyze. More than often, these images are analyzed by human experts such as pathologists and physicians. ...
  • Performance-aware design-space optimization and attack mitigation for emerging heterogeneous architectures 
    Sinha, Mitali; Deb, Sujay (Advisor) (IIIT-Delhi, 2022-04)
    In recent years, as multi-core processors are emerging as a solution to the limitations of power scaling, the software domain is also experiencing a surge of compute and data-intensive applications. These applications are ...
  • A practical methodology to waive marginal timing violations using machine learning 
    Kumar, Rajat; Saurabh, Sneh (Advisor) (IIIT-Delhi, 2022-07)
    Achieving timing closure is a challenging task, and it becomes more complicated due to the artificial pessimism in the traditional timing models of the flip-flops. During the signoff stages, we can alleviate this problem ...
  • Question answering system based on sentence similarity 
    Kashif, Mohammed; Arora, Chetan (Advisor) (2017-06)
    Question-Answering systems are becoming increasingly popular, especially after the advent of Machine Learning. Such systems can be used in a wide variety of applications ranging from Open domain question answering or closed ...
  • Security evaluation and implementation of facial recognition algorithms 
    Dwivedi, Purusharth; Chang, Donghoon (Advisor) (IIIT-Delhi, 2017-11-17)
    The following report discusses various facial recognition spoofing techniques in use today, and compares various algorithms, that have been developed for detecting the same. Continuing towards the previous semester’s ...
  • Techniques for automating quality assessment of context-specific content on social media services 
    Dewan, Prateek; Kumaraguru, Ponnurangam (Advisor) (IIIT-Delhi, 2017-08)
    Online Social Networks have become a cornerstone of Web 2.0 era. Internet users around the world use Online Social Networks as primary sources to consume news, updates, and information about events around the world. However, ...

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