Predicting Split Decisions in MPEG-2 to HEVC Video Transcoding by Shanableh, Tamer

“…While in the transcoding mode, the split decisions of coding units of the HEVC video are predicted. Two formulations are proposed for the prediction of split decisions based on multi model and multi-tier solutions. …”
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Exploring Machine Learning Models to Predict Harmonized System Code by AL Taheri, Fatma

“…The results of the study indicate that machine learning models are effective tools in predicting HS Code for the user goods descriptions. …”
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Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques by Hassan, Mahitab Alaaeldin

“…A Master of Science thesis in Computer Engineering by Mahitab Alaaeldin Hassan entitled, "Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques," submitted in May 2017. …”
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Predicting split decisions of coding units in HEVC video compression using machine learning techniques by Hassan, Mahitab Alaaeldin

“…The generated models at each coding depth are then used to predict the split decisions of subsequent coding units. …”
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Detecting Code Smells by Jammal, Rim El

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Long non-coding RNA AC099850.4 correlates with advanced disease state and predicts worse prognosis in triple-negative breast cancer by Radhakrishnan Vishnubalaji (3563306)

“…<p dir="ltr">Our understanding of the function of long non-coding RNAs (lncRNAs) in health and disease states has evolved over the past decades due to the many advances in genome research. …”

Fast methods for code search in CELP by Ahmed, M.E.

“…The code excited linear prediction (CELP) technique has the potential for producing high quality synthetic speech at bit rates as low as 4.8 kb/s. …”
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Sequence MAP decoding of trellis codes for Gaussian and Rayleighchannels by Al-Semari, S.A.

“…The second part of the paper considers trellis encoding of the code-excited linear predictive (CELP) speech coder's line spectral parameters (LSPs) with four-dimensional (4-D) QPSK modulation. …”
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Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory by Nadia Rasheed (22997257)

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Warped ARMA filters in high quality audio coding by Deriche, M.

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Data Embedding in Scrambled Video by Rotating Motion Vectors by Ahmed, Afaf Eltayeb Mohamedelbagir

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CNN and HEVC Video Coding Features for Static Video Summarization by Issa, Obada

“…We preprocessed the well-known video datasets by coding them using the HEVC video coding standard. …”
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MPEG-2 to HEVC Video Transcoding With Content-Based Modeling by Shanableh, Tamer

“…The objective of the transcoder is to migrate the abundant MPEG-2 video content to the emerging HEVC video coding standard. The transcoder introduces a content-based machine learning solution to predict the depth of the final HEVC coding units. …”
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Altering Split Decisions of Coding Units for Message Embedding in HEVC by Shanableh, Tamer

“…The encoder starts by computing a mapping between the split decisions of a Coding Unit (CU) and its features variables. This results in model weights that can be used to predict the split decisions. …”
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High speed multi-stage code search algorithm in CELP by Elshafei, M.

“…An efficient multistage algorithm for code search in the code excited linear prediction (CELP) methods of speech coding is described. …”
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LNCRI: Long Non-Coding RNA Identifier in Multiple Species by Saleh Musleh (15279190)

“…<p>The pervasive nature of long non-coding RNA (lncRNA) transcription in the mammalian genomes has changed our protein-centric view of genomes. …”

HEVC Video Encryption with High Capacity Message Embedding by Altering Picture Reference Indices and Motion Vectors by Shanableh, Tamer

“…To extract message bits, an authorized decoder builds a classification model per video sequence and uses it for predicting the true values of the reference indices and motion vectors. …”
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Large language models for code completion: A systematic literature review by Rasha Ahmad Husein (19744756)

“…Our analysis reveals that LLMs significantly enhance code completion performance across several programming languages and contexts, and their capability to predict relevant code snippets based on context and partial input boosts developer productivity substantially.…”

PredictPTB: an interpretable preterm birth prediction model using attention-based recurrent neural networks by Rawan AlSaad (14159019)

“…</p><h3>Methods</h3><p dir="ltr">The architecture of PredictPTB employs recurrent neural networks (RNNs) to model the longitudinal patient’s EHR visits and exploits a single code-level attention mechanism to improve the predictive performance, while providing temporal code-level and visit-level explanations for the prediction results. …”

Emerging roles of the long non-coding RNA NEAT1 in gynecologic cancers by Maryam Farzaneh (17788460)

“…Therefore, NEAT1 may function as a potent biomarker for the prediction and treatment of breast, ovarian, cervical, and endometrial cancers. …”