Results 131 to 140 of about 343,225 (391)

Product differentiation in the fruit industry: Lessons from trademarked apples

Agribusiness, EarlyView.
Abstract We derive price premiums for patented or trademarked apple varieties, also known as “club apples,” compared to open‐variety apples. We use an expansive retail scanner dataset, along with unique data on apple taste characteristics, to estimate monthly club apple premiums for 2008–2018.
Modhurima Dey Amin, Syed Badruddoza, Jill J. McCluskey, Gregory Astill   +3 more
wiley   +1 more source

Diversification Based Static Index Pruning - Application to Temporal Collections

, 2013
Nowadays, web archives preserve the history of large portions of the web. As medias are shifting from printed to digital editions, accessing these huge information sources is drawing increasingly more attention from national and international ...
Gançarski, Stéphane, Pehlivan, Zeynep, Piwowarski, Benjamin   +2 more
core   +1 more source

Charting the Path to Increased Oil Palm Output in Ghana Beyond Area Expansion: Technology or Managerial Capacity — Which Leads the Way?

Agribusiness, EarlyView.
ABSTRACT This study sets out to investigate the prospects for raising oil palm output in sub‐Saharan Africa, particularly Ghana, without further expansion of cropland. Given global concerns about oil palm's role in deforestation and land use change, the focus is on enhancing productivity on existing farmlands.
Jacob Asravor, Francis Tsiboe, Ayobami Adetoyinbo, Jacob Ankamah   +3 more
wiley   +1 more source

Hybrid rule‐based and optimization‐driven framework for the synthesis of end‐to‐end optimal pharmaceutical processes

AIChE Journal, EarlyView.
Abstract The modernization of pharmaceutical manufacturing is driving a shift from traditional batch processing to continuous alternatives. Synthesizing end‐to‐end optimal (E2EO) manufacturing routes is crucial for the pharmaceutical industry, especially when considering multiple operating modes—such as batch, continuous, or hybrid (containing both ...
Yash Barhate, Daniel J. Laky, Daniel Casas‐Orozco, Gintaras V. Reklaitis, Zoltan K. Nagy   +4 more
wiley   +1 more source

Widened Attention‐Enhanced Atrous Convolutional Network for Efficient Embedded Vision Applications under Resource Constraints

Advanced Intelligent Systems, EarlyView.
The article introduces WACEfNet, a new convolutional neural network architecture optimized for efficient aerial image analysis under resource constraints. It creatively integrates attention mechanisms and atrous convolutions into a compact widened residual network framework.
Md Meftahul Ferdaus, Mahdi Abdelguerfi, Kendall N. Niles, Ken Pathak, Joe Tom   +4 more
wiley   +1 more source

Really should we pruning after model be totally trained? Pruning based on a small amount of training [PDF]

arXiv, 2019
Pre-training of models in pruning algorithms plays an important role in pruning decision-making. We find that excessive pre-training is not necessary for pruning algorithms. According to this idea, we propose a pruning algorithm---Incremental pruning based on less training (IPLT).
arxiv  

Generative Inverse Design of Metamaterials with Functional Responses by Interpretable Learning

Advanced Intelligent Systems, EarlyView.
This work introduces random‐forest‐based interpretable generative inverse design (RIGID), a new single‐shot inverse design method for metamaterials using interpretable machine learning and Markov chain Monte Carlo sampling. Once trained on a small dataset, RIGID can estimate the likelihood of designs achieving target behaviors (e.g., wave‐based ...
Wei (Wayne) Chen, Rachel Sun, Doksoo Lee, Carlos M. Portela, Wei Chen   +4 more
wiley   +1 more source

Connection pruning with static and adaptive pruning schedules

Neurocomputing, 1997
Abstract Neural network pruning methods on the level of individual network parameters (e.g. connection weights) can improve generalization, as is shown in this empirical study. However, an open problem in the pruning methods known today (e.g. OBD, OBS, autoprune, epsiprune) is the selection of the number of parameters to be removed in each pruning ...
openaire   +4 more sources

The Generalization-Stability Tradeoff In Neural Network Pruning [PDF]

arXiv, 2019
Pruning neural network parameters is often viewed as a means to compress models, but pruning has also been motivated by the desire to prevent overfitting. This motivation is particularly relevant given the perhaps surprising observation that a wide variety of pruning approaches increase test accuracy despite sometimes massive reductions in parameter ...
arxiv  

DSA: More Efficient Budgeted Pruning via Differentiable Sparsity Allocation [PDF]

arXiv, 2020
Budgeted pruning is the problem of pruning under resource constraints. In budgeted pruning, how to distribute the resources across layers (i.e., sparsity allocation) is the key problem. Traditional methods solve it by discretely searching for the layer-wise pruning ratios, which lacks efficiency.
arxiv