companydirectorylist.com  Global Business Directories and Company Directories
Search Business,Company,Industry :


Country Lists
USA Company Directories
Canada Business Lists
Australia Business Directories
France Company Lists
Italy Company Lists
Spain Company Directories
Switzerland Business Lists
Austria Company Directories
Belgium Business Directories
Hong Kong Company Lists
China Business Lists
Taiwan Company Lists
United Arab Emirates Company Directories


Industry Catalogs
USA Industry Directories












Company Directories & Business Directories

ASPHALTE DALLAIRE & ST-PIERRE

SAINT-FELICIEN-Canada

Company Name:
Corporate Name:
ASPHALTE DALLAIRE & ST-PIERRE
Company Title:  
Company Description:  
Keywords to Search:  
Company Address: 1123 Boul Sacre-Coeur,SAINT-FELICIEN,QC,Canada 
ZIP Code:
Postal Code:
G8K1P9 
Telephone Number: 4186798825 
Fax Number: 4186790980 
Website:
 
Email:
 
USA SIC Code(Standard Industrial Classification Code):
161101 
USA SIC Description:
Paving Contractors 
Number of Employees:
1 to 4 
Sales Amount:
$500,000 to $1 million 
Credit History:
Credit Report:
Very Good 
Contact Person:
Jean-Paul Demers 
Remove my name



copy and paste this google map to your website or blog!

Press copy button and paste into your blog or website.
(Please switch to 'HTML' mode when posting into your blog. Examples:
WordPress Example, Blogger Example)









Input Form:Deal with this potential dealer,buyer,seller,supplier,manufacturer,exporter,importer

(Any information to deal,buy, sell, quote for products or service)

Your Subject:
Your Comment or Review:
Security Code:



Previous company profile:
ASSOCIATION CHASSE & PECHE ST FELICI
ASSOCIATION CHASSE & PECHE
ASPHALTE DALLAIRE & ST PIERRE INC ASPH
Next company profile:
ASPHALTE B R INC
ART DE LA BEAUTE
ARMOIRES ST FELICIEN










Company News:
  • Counterfactual Debiasing for Fact Verification
    579 In this paper, we have proposed a novel counter- factual framework CLEVER for debiasing fact- checking models Unlike existing works, CLEVER is augmentation-free and mitigates biases on infer- ence stage In CLEVER, the claim-evidence fusion model and the claim-only model are independently trained to capture the corresponding information
  • DEBERTA: DECODING-ENHANCED BERT WITH DISENTANGLED ATTENTION - OpenReview
    Recent progress in pre-trained neural language models has significantly improved the performance of many natural language processing (NLP) tasks In this paper we propose a new model architecture DeBERTa (Decoding-enhanced BERT with disentangled attention) that improves the BERT and RoBERTa models using two novel techniques The first is the disentangled attention mechanism, where each word is
  • Weakly-Supervised Affordance Grounding Guided by Part-Level. . .
    In this work, we focus on the task of weakly supervised affordance grounding, where a model is trained to identify affordance regions on objects using human-object interaction images and egocentric
  • FreeVS: Generative View Synthesis on Free Driving Trajectory
    Novelty Clever use of pseudo-images obtained through colored point cloud projection as a unified representation for all view priors, simplifying the learning objective for the generative model Evaluation Introduces two new challenging benchmarks - novel camera synthesis and novel trajectory synthesis Efficiency The authors claim it takes less computational resources at inference time
  • Training Large Language Model to Reason in a Continuous Latent Space
    Large language models are restricted to reason in the “language space”, where they typically express the reasoning process with a chain-of-thoughts (CoT) to solve a complex reasoning problem
  • Diffusion Generative Modeling for Spatially Resolved Gene. . .
    Weakness 3 (Novelty) The proposed method seems like a clever application of conditional diffusion models to the problem Can the authors further comment on the novelty of their method and how is it different compared to the existing literature? Thank you for allowing us to further clarify the novelty of Stem compared with existing methods
  • Semi-supervised Camouflaged Object Detection from Noisy Data
    1 The Pixel-level loss reweighting method is more clever, but the integrated learning using two network fusion feature designs is too bloated 2 The paper proposes for the first time the use of semi-supervised learning to solve the problems of noisy labels and difficulty in obtaining labels in Camouflaged Object Detection 3 The paper makes a
  • SleepSMC: Ubiquitous Sleep Staging via Supervised Multimodal . . .
    Sleep staging is critical for assessing sleep quality and tracking health Polysomnography (PSG) provides comprehensive multimodal sleep-related information, but its complexity and impracticality
  • KnowTrace: Explicit Knowledge Tracing for Structured. . .
    " This paper introduces a clever incorporation of knowledge graph operation for structured RAG " (Reviewer ifaQ) " The proposed method is straightforward, intuitive, and easy to implement "; " It is innovative that the paper leverages the structured nature of reasoning paths to filter and refine generated trajectories for model training




Business Directories,Company Directories
Business Directories,Company Directories copyright ©2005-2012 
disclaimer